By Swanand Jawadekar

Today, smart machines have become one of the integral parts of smart factories leading to the Industry 4.0 revolution. This paper details solutions developed for special purpose machines such as cartooning machines, tube filling machines and can be extended to similar types of SPM's. These machines perform specialized manufacturing operations and are integral parts of agriculture, pharmaceutical or industrial factories.

The Solution capitalizes on the readily generated engineering data in conjunction with loT (Internet of things) and AR (Augmented Reality) to make the machine smarter in a connected environment. It uses operating data from the equipment to predict various functional parameters such as production and performance analysis, energy analytics, delivering new insights towards Overall Equipment Effectiveness (OEE).

Design and Development: Critical Foundation

Today, the Digital twin has become an integral part of the manufacturing process. It can be characterized as a digital representation of the physical asset, which enables additional insight into machines' performance.

Besides supporting design strength analysis, it provides tools to examine the operating mechanism, loads and boundary condition, failure studies, alternate material. Carrying out a mechanism’s kinematic analysis involves calculating the velocity, location, and acceleration of any of its points or links for the prescribed time step. The study helps the user understand the mechanism's behavior and make changes in geometry, material, and improve product performance.

For any machine performance evaluation, mechanisms play a critical role. From material entry to final product manufacture, there are various mechanisms involved, consisting of combinations of conveyers, Cam, and rollers. Apart from analyzing critical mechanism parameters, Digital twin can be effectively used to identify influential data parameters affecting machine performance which can be further monitored using loT Techniques. The parameter identification will help the user effectively use sensors, location, and data acquisition and connect to the mobile portal. Once the critical parameter has been identified and equipped with sensors, they can measure the real-time mechanical or heat load which the machine experience in real life. Based upon received data, one can predict component failure, and the same can be replaced much before the break or worn out.

Data Anytime / Anywhere

Currently, most customers are looking towards intuitive products, easy to interact with, and high on performance parameters. Smart machines effectively use loT tools and parameters identified from Design simulations to provide a robust tracking mechanism. As determined by validation studies, critical machine design parameters can be further monitored to achieve better insight into machine performance. The performance tracker data can be accessed from a remote location and enhances the support system's reach. IoT also helps the customer for a better post-sale experience and optimized environment.

Following are some of the typical machine performance parameters which can be tracked live:

1. Live KPI's and dashboards for real-time monitoring of machines
2. OEE, Performance, Availability
3. Process, Production, Energy Analysis

Augmented Reality

Augmented reality is gaining momentum in the marketplace and has shown incredible potential to support enterprise activities with different departments to perform their operations efficiently. It promotes a converged experience for the 3D AR content to Visualize, Instruct, simulate the working environment. The approach embeds desired parameters from the loT platform in the AR experience helps visualize a machine's real-time information. AR studies can further be synched with various levels of an organization as illustrated below:

• Design and development: collaborative design review, Hand-hold training
• Manufacturing: service and technical manual, work instructions manual, performance dashboard, operator instruction, better response to any of internal request, higher safety and security, real-time of the shop floor experience
• Market (Creating virtual product experience)

In the Nutshell

Design engineering has evolved dramatically. From draft board design to Computer-Aided Design and modeling to virtual reality, it has crossed global boundaries. With old proven CAD techniques and new Data, AR/VR (augmented and virtual reality) tools, we support international customers to build their design faster, better, and accessible / monitor from remote locations. These solutions extend flexibility to the customer and bring the global design team to work together towards standard global.

By Swanand Javadekar

Preface

The automotive industry has been facing a daunted set of challenges with upcoming connected cars, autonomous driving, and electric vehicles. It is an opportunity to differentiate for the right minds by bringing the right mix of solutions to the customer and enlightening them with more intelligent products. The following paper highlights the association of technology trends to design connected products and build efficient ecosystems for execution. Some of the aspects discussed are

• Anticipate customer needs and move from classical design mindset (collaborative designs)
• Mechanical to mechatronics (CAD to AR)
• How products are used in the field to differentiate and competitiveness of products (Insights)

Trends

There are various ways technology is changing product outlook, following are some of the exciting trends influencing product design and development cycle:

• For many years, the typical development cycle for automotive was @ 3-4 years. With the advancement of CAD and other related tools, the same has been reduced to 1.5-2 years. Even In such a scenario, the designer still has to wait for actual testing results and production cycle to get the product performance feedback. The designer can work on a live project with a feedback loop system with advanced software and sensors. For the newly launched car model, the designer will swiftly get feedback to implement optimization changes. In contrast, the older model performance can be tuned based upon the much realistic availability of load data.
• The designer will be working to build more customer-centric automotive models. He will be able to assess various patterns based on driving habits. This pattern will help him adjust, manage and tune various critical auto components to performance needs such as powertrain and engines.
• Data blending will become a more significant challenge as the designer receives and reviews data from various sources. Apart from the traditional data sources such as design, CAD data, validation, he will also collect/collate additional analytical data from sensors towards assembly performance, failure prediction, and vehicle running data. The appropriate data analytics tools need to be used for the correct outcome to be incorporated as the design parameters.

 Smart Products: 4 promoting factors

Today, Smart Products have become one of the integral parts of our life. It changes the way we use products and generates new business models. This paper details layout developed to build intelligent products and discusses the contribution and trends in each sector. The discussion is limited to product design and development and not extended to manufacturing 4.0

In a connected environment, smart products use the basic engineering data in conjunction with loT (Internet of things) / AR (Augmented Reality), embedded systems, and data analytics to provide better insight to the user and a machine manufacturer. It uses operating data from the equipment and uses a feedback loop effectively to predict various functional parameters related to product performance.

Designing smart products

As a designer who builds innovative products, he uses various advanced tools such as MBD (model- based engineering) and DEM (differential element method) to generate better insight into component behavior.

Digital twin, which generates buzz across the engineering community, is a virtual replica of a product containing representative mechanical, electrical, electronic, and performance configuration information. The digital twin is not new, as the design community is already using various CAD, CAE, and CAM tools for the past few years. However, it has witnessed changes in the ability to collect, collate and analyze big data, work towards finding trends, anomalies and use the feedback loop back to design context to make it robust. Building digital twin also leads to effectively monitoring data, leading to building newer business models.

Simulation is also one of the data-driven tools extensively used to analyze components, from simple durability to complex crash simulation. With higher computing power, the data handling capacity has been increased, as it can handle complete vehicle analysis compared to component level validation. Today, ROM (reduced-order method) based models have been used, which are machine learning solutions for reducing the size of a data set while preserving the essential parts of the information contained within that data. Such an approach now supports the user to analyze the components for rapid execution, reducing the total number of runs. There are various methods for which data analysis techniques are used: fault detection, predictive maintenance, statistical monitoring, real-time crash, and safety.

Designing connected products: AR/VR

Today AR/VR is playing a significant role in automotive product design and development. Typically, AR/VR can be extensively used for design and development, manufacturing, marketing, training, and servicing. More usage of these techniques is applied towards manufacturing and marketing, but the practice of product design is on the rise. Someone can effectively use these techniques used for design reviews and revision comparison. With the latest external devices such as hololens available in the market, the user can get an immersed view of the design for detailed assessment.

Designing Embedded products: ADAS

It's exciting to note how these four verticals complement each other for product feature enhancement. Let's take the example of embedded system / ADAS (advanced driver-assisted systems). We have seen that, typically, engineering simulation has been used for product development and digital twins, but the usage can be extended towards ADAS development. Some of the scenarios where validation tools can support to improve product performance understanding are semiconductor simulation (reliability analysis of Printed circuit board, energy consumption), sensor simulation (radar pattern simulation, placement of sensors compared to signal integrity), and driving scenario (software algorithm modeling simulation)

Designing insightful products

We know that Data analytics tools are effectively used for supply chain optimization, marketing mix analysis, user and dealer satisfaction, and customer behavior analysis. How can it be effectively used for a designer to view insight at an early stage?

Today product designers are facing challenges towards converting data to actionable insights. The designer will work on three types of data, design data (based upon engineering calculations), test or proving data (standard vehicle test data), and real-life running data (received via various sensors loaded at designer vehicle test points). Multiple data analysis tools/algorithms will support to decode the data effectively and will support designer to take early decisions such as component failure prediction, feature management (leads to customization of platforms).

Getting Act Together

As mentioned in the above column, various technologies work seamlessly to build a better and more innovative product. Let's discuss a few examples of how companies use a combination of technologies to build a newer customer experience.

Design proposal selection

Today Tier1 suppliers are interacting with OEM to select their various design proposals. With AR/hololens, the supplier can offer a better immersive experience to the customer. It also helps end customers select design proposals much swiftly, saving time and money. For example, automotive interior tier 1 suppliers can envision and demonstrate "Instrument panel" fitments within the car environment to OEM's. With changes in color scheme, shading, feature recognition, the end customer can envisage effectively for better selection.

Light-weighting

• lightweight material construction – Reinforced @ unreinforced plastic/sheet molded composites (SMC)
• Structural lightweights – tailored welded blanks/profile and tubular structure
• optimized production process – reduced no of weld spots, rivet/light joining techniques

In summary

Automotive product design has expanded beyond CAD, and advanced tools have been implemented in the early stage of the design cycle. It assures various benefits to designers such as better understanding of product behavior, customer-centric innovative design, and shortens design cycle, saving time and money.

By Swanand Javadekar

A digital twin is a dynamic representation of an asset that allows us to understand the better working of the system and predict performance for better design directions. A product configurator is a dynamic representation of the CAD model that allows us to build an intelligent, practical model to enhance the speed of design and development. This paper conceives the concept and applies it to functional scenarios for better understanding and elaboration.

Let us quickly elaborate on both the concepts and explore further for combined application:

Product Configurator

Product Configurator is a single solution that can,

• Manage thousands of your product variants
• Allow your customers to configure your products
• Allow your customers to access relevant CAD data
• Help your sales team respond quickly to inquiries
• Make your design team more productive

Essentially, it's a solution that helps you get more customers and dramatically increases the productivity of your sales and design team. A product configurator is a design automation solution that works on parameter-driven design. We can create a complete model on the fly by entering a few key parameters. Our Product Configurator solution is based on proven and tested CAD neutral architecture. Hence we can work with the CAD system you use (NX, SolidEdge, SolidWorks, Creo (Pro/E), AutoCAD, Autodesk Inventor, and others).

Digital Twin

As mentioned earlier, a digital twin is a virtual representation of an actual world entity or a system to understand product behavior better. Generally, we can divide digital twin into three categories:

• Product digital twin: This approach is typically applied to a product and its performance and has been used by reasserting team. The concept has been ably supported by product simulation leads to the simulation-based digital twin. In such a case, the product performance is checked live, and necessary design can be made on the fly.
• Performance digital twin: this type of approach is used to manage operational cost and end- user use. This has been used by the maintenance and service department.
• Process Digital twin: Another primary application of digital twin lies with manufacturing operations, i.e., to reduce wastage, enhance yield. The owner of such exercise is typically the line manager or plant head.

Case Study: Industrial Engineering (Elevator)

The product configurator and the digital twin have applications at various levels, typically in operations, commissioning, and installations.

If we divide elevator methods and processes into three categories: Install, Operate, Maintain, we will elaborate areas where the standard approach will be helpful.

Product configurator can be used to build a CAD model based on available configuration parameters such as allotted space, cage parameters, and internal and external dimensions. The cad model will be ready based upon various options, which can be easily used further for manufacturing drawings or product validation. Once your multiple models are available, the same can be used for further meshing and validation to pick the best-suited configuration. We can calculate the remaining useful life (RUL) and any what-if scenario. With confirmation from the product validation exercise, the final model can be used for further AR/VR exercise for product visualization purposes.

Product configurator and digital twin combination will provide faster product development; the final product can also be used for further downstream applications such as AR/VR. Not only does the product manufacturer benefit by delivering a superior product, but other supporting systems such as building, and infrastructure management will benefit from the optimized maintenance cost and less downtime.

Case Study: Industrial Engineering (Furniture)

The furniture industry is an exciting example involving engineering with style and substance. The customer is demanding in terms of various options or variants, and the possibilities are endless. It's where science meets the art, and probabilities are limitless.

If we take the example of a simple chair, the flow chart is quite exhaustive:

All the combinations come with the additional complexity of colors, mesh size, etc. In such a case where the manufacturer provides exhaustive options, and customers make customizable chairs, a combination of Product configurator and digital twin offers dynamic support to realize the dream. The CAD model of a chair combination is made faster while tested with the furniture industry-standard of weights. Any unique composite structure design or material changes can also be realized quickly. It allows the manufacturer to release the product faster to customer delight.

Combining Product configurator and digital twin is the way forward as it allows manufacturers to manufacture faster to market methodology and offers customers to choose from a wide variety of options leading to customer delight.

Cloud computing, or the on-demand availability of computer system resources, has recently taken the world by storm, with cloud providers like Alicloud, AWS, IBM, Google, Microsoft Azure, and Oracle creating Software-as-a-Service, Marketing-as-a-Service, Analytics-as-a-Service, and now Infrastructure-as-a-Service, amongst others, to capture the seemingly insatiable customer demand for services. Whether a business should go with a private cloud, a public cloud, an omnicloud, or a hybrid cloud aren't quickly answered without understanding a company's current set-up and its potential future IT demands.

The hybrid cloud creates a single IT infrastructure that runs its applications, systems, and workloads. It joins a company's on-premises private cloud services with a third-party, public cloud, which gives an organization the ability to select optimal cloud providers for each application, container, or workload and move freely between the two clouds as circumstances and situations change. Some popular third-party vendors like AWS, IBM, Microsoft, Alibaba, and Google, provide their cloud services over the public Internet.

Unavailable to the public, private clouds are hosted on-premises and provide businesses with many benefits of a public cloud, i.e., self-service usage, scalability, elasticity, and robust security measures. The fundamental difference between a private and a public cloud is the level of responsibility needed to run them. The IT department of the company hosting the private cloud takes care of all the private cloud's staffing, cost, accountability, and maintenance expenses.

Public clouds, however, are provided over the Internet by a third-party vendor, who charges by consumption, either by CPU, storage, bandwidth, software usage, or a combination of them. Public clouds numb down the cost and hassle of buying, operating, and maintaining on-prem hardware infrastructure and application. The cloud service provider supports and manages the system. Deployment is fast on a public cloud, scalability is almost infinite, the cost is easily controlled, and the system can be highly secure.

The hybrid cloud lets an organization choose between multiple cloud providers depending on which company specializes in a particular area. For example, an organization looking for a robust AI platform might go for Google Cloud because TensorFlow is a powerful Google AI tool that would seamlessly add to Google's cloud offerings. Companies looking to utilize Excel, Word, Visual Basic, or Microsoft Teams might choose Azure because it's owned by Microsoft and would probably be the most cost-effective option. Because every implementation is unique and so many variables go into building a cloud solution, organizations should shop around and piece together their solution keeping in mind the advantages and disadvantages of each cloud provider.

Traditional hybrid cloud architecture used to come as unsophisticated pre-packaged options, but today's hybrid cloud architecture is highly focused on supporting the portability of workloads across all cloud environments. Containers and microservice architecture are simplifying the deployment of workloads across multiple cloud options. This approach utilizes a single application composed of many loosely coupled, independently deployable, and reusable more minor services. These applications are being deployed in lightweight containers, including executable units containing both the application code and the virtualized operating system dependencies needed to run everything.

Today, the line between public and private clouds is blurring. Public clouds are now going private, and private clouds are going public, but a coalescence is coming. Many cloud vendors now offer on-premises public cloud services that run on a customer's site. Private clouds can now be found at off-premises data centers, virtual private clouds (VPCs), virtual private networks (VPNs), or even rented from third-party providers. At the same time, a container orchestration platform automates application deployment across multiple cloud establishments. 

The hybrid cloud has many benefits. At a time when the work-from-home revolution is growing, hybrid clouds can help support a remote workforce. Organizations can reduce IT costs as well as improve scalability, increase collaboration, and enhance innovation. Hybrid clouds provide better business continuity while increasing agility. Counter-intuitively hybrid clouds can improve security and risk management. When jumping into the cloud, an organization is partnering with companies whose very existence is threatened if their security fails. For companies looking to take the next step in their digital transformation, a look to the hybrid cloud is in order. 

Manufacturing and construction have witnessed significant reforms in a fast-changing world. Newer processes, machines are coming up with more unique means of operation, management, and increased efficiency. Remember, time is a valuable asset in today’s world.

Additive manufacturing (AM), also known as 3D printing, is a computer-operated approach to construction and industrial production.

Additive manufacturing is a computer-operated and controlled system that creates three-dimensional objects by carefully sequentially depositing various material compositions in layers.
A comprehensive digital layout is fed as design data, and the machine operates accordingly. Additive manufacturing is mainly used for making rapid prototypes and forging complex geometric objects.
The other names for Additive Manufacturing are 3D printing, Additive Layer Manufacturing.

Working Principle

Conventional methods employ lengthy processes which are time-consuming and prone to errors. Traditional methods of creating an object include material removal through machining, milling, carving, shaping, etc.

Additive manufacturing brings in more pro-manufacturing method that differs significantly from subtractive, conventional manufacturing methods.

For example, while the conventional method involves milling a work object from a solid block, additive manufacturing forges the part layer by layer from fine powders fed as materials. Things such as various metals, polymers, and composite materials can be used for 3D printing. The operational directives are provided by computer-aided design (CAD) data or 3D scanners that drive the machine in precise geometric patterns to deposit materials layer by layer.

The primary constituents of additive manufacturing technology are:

• Computer
• Computer-Aided Design or CAD software
• Machine equipment
• Layering material

Once the CAD data is lodged in, the computer guides AM machine to read the CAD data and lay down layer upon layer of various materials, usually in powdered & liquid form, to create a 3D object as intended.

In simple terms, additive manufacturing works like an “aircraft on autopilot.”

Commercialization of 3D printers

Additive manufacturing is not an archaic process, but rather, it came up in the ’80s. Here is a point-by-point history of AM in chronological order:

The 80’s:

The first commercial use of additive manufacturing with stereolithography from 3D Systems. The SLA-1 was the first commercially released AM machine. Ciba-Geigy partnered with 3D Systems for SL material development and commercialized acrylate resins. DuPont’s Somos stereolithography machine also entered the market in the same year. Japan’s NTT Data CMET and Sony/D-MEC commercialize stereolithography.

The 90’s:

Germany’s Electro-Optical Systems sells the first stereolithography system. Quadrax introduces Nark 1000 SL system. Three AM technologies, fused deposition modeling (FDM) from Stratasys, solid ground curing (SGC) from Cubital, and laminated object manufacturing (LOM) from Helisys, were commercialized. Selective laser sintering (SLS) and Soliform stereolithography system from Teijin Seiki were commercialized. Soligen commercialized direct shell production casting (DSPC), which used an inkjet mechanism. This year saw a bunch of new additives manufacturing systems. ModelMaker from Solidscape, Solid Center from Kira Corp., or EOSINT by EOS were examples. This year saw 3D Systems sell its first 3D printer called Actua 2100 that used an inkjet printing mechanism that deposited wax materials layer by layer. AeroMet was founded as a subsidiary of MTS systems corp. The company developed a laser additive manufacturing (LAM) process that used high-power laser and titanium alloys. Optomec commercializes laser-engineered net shaping (LENS).

The early 2000’s:

This year saw the emergence of new technologies. Quadra by Object Geometries, Sanders Prototype (now Solidscape) by PatternMaster, and Z402C machine by Z Corp. (World’s first commercially available multi-color 3D printer). Generis GmbH from Germany introduced its extensive GS 1500 system. ProMetal installed its first RTS-300 machine in Europe. Stratasys sells its Dimension product for $29,900. Solidscape introduced the T66 product while Phenix Systems of France sold Phenix 900 system for the first time. Later on, Stratasys signs an agreement with Arcam to be the exclusive distributor in North America for electron beam melting (EBM) systems. Dimension 1200 BST, NanoTool, InVision DP, Accura 60 photopolymer, Formiga P 100 laser-sintering system, SEMplice LSM, V-Flash 3D printers, ZPrinter 450, A2 electron Beam melting machine were some of the groundbreaking AM machines introduced in the early 2000s.

The late 2000’s:

EuroMold, SLM Solutions present SLM 280 HL. CRP Technology announced Windform GF 2.0, while 3D Systems unveiled a smaller 3D printer, the ProJet 1000, for $10,900. In 2012, MakerBot released the MakerBot replicator. EasyClad from France introduced the MAGIC LF600 AM machine in 2012. Solidoodle from NY released Soldoodle 3D printer wild Belgium based Materialise introduced Magics 17. The late 2000’s So the growth of additive manufacturing and the 3D printing machine market. The AM or 3D printing Industry witnessed massive investment. In September 2013, Voxeljet announced its $100 million IPO plan. In March 2015, ExOne released Exerial, a large machine with multiple stations to enable continuous production. Early 3D printers were not very light and convenient to handle. It is only after the advent of the 21st century that they have become more affordable, straightforward, easy to operate, and versatile enough to be used in a wide range of operation ranging from tools & Page 4 of 1 component manufacture, electronics, metalwork, polymers, and product prototypes. Past three years, there has been a tendency to employ 3D printing and AM tech in the real estate industry.

We can see how fast Additive manufacturing emerged within just three decades and how it is relevant across multiple industrial verticals today. Whether it is about building prototypes, constructing affordable housing or producing components, AM and 3D printing have offered effective systems that triumph over traditional methods.
This technology enables faster product development and market entry, smoother product customization, and seamless integration at lesser cost and time. Thus, additive manufacturing provides OEM manufacturers an excellent opportunity to unleash their products at a higher rate at much lesser expenses for great returns and better customer benefits while ensuring sustainability.

Reference:

Wohlers, T. and Gornet, T., (2016). History of additive manufacturing, Wohlers Report 2016. Retrieved from https://docplayer.net/13470116-History-of-additive-manufacturing.html

As marketers and managers know, the challenges and excitement of pharmaceutical product launches are potentially as profitable for companies as they are beneficial for patients. Nonetheless, careful planning and resourcefulness are instrumental in developing a corporate roadmap for new products. Executing a launch well means that a new pharma product is more likely to become a market leader.
Below, we discuss how to achieve success through a sophisticated approach involving influence mapping tools. Read on to discover more, including an overview of today's leading software systems. Armed with this information, your pharmaceutical company can harness the power of Artificial Intelligence or AI in development projects, product launches and sales campaigns.

Facing the challenges

The different stages in the path from R&D to product launch frequently involve various teams and functions. Although the groups involved often share similar goals, they tend to operate in a degree of isolation.

At each stage, experts address a relatively narrow set of challenges related to their immediate responsibilities. Though the best amongst them will endeavor to consider the broader situation wherever possible, there may sometimes be little incentive to do so. In some cases, short-term conflicts can arise.
In contrast, the safe development of effective drugs, medicines and appliances is, of course, multidisciplinary. It involves research and collaboration, combining the efforts of multiple departments - sometimes in different countries.

Apart from an in-depth knowledge of the disease area concerned, medical professionals within a company need to remain keenly aware of patient care and stakeholder expectations. Achieving this delicate balance requires thoughtfulness, accurate information, well-developed commercial insight and, of course, interpersonal skills.

Making informed decisions

Remaining competitive requires the linking of clinical results to patient outcomes. For instance, when customer service and support representatives or teams liaise with healthcare providers, they may well uncover unmet patient needs.

A cross-functional approach between commercial, clinical and regulatory elements should also research treatment outcomes, hear input from patient's representatives and communicate with public and investor relations.

Maximizing return on investment

Remaining competitive requires the linking of clinical results to patient outcomes. For instance, when customer service and support representatives or teams liaise with healthcare providers, they may well uncover unmet patient needs.

Similarly, valuable insights might emerge regarding patient's acceptance of products, revealing untapped market potential and enabling additional clinical programmes to boost ROI.

Deploying AI in the pharmaceutical sector

Before the advent of specialist software, spreadsheets proliferated. Unfortunately, information sets frequently overlapped and version control was inconsistent. As a result, Influence mapping was hit and miss; links between connections were cumbersome to set up and challenging to maintain.

Examples of problems and quirks included:

• Staff was unaware of who had visited a setting.
• No up-to-date or reliable contact information was available regarding external entities.
• Inefficiencies and frustration stemmed from repeated requests for the same details from clients.
• Multiple medicines in one company saw different teams service the same account.
• Helpful information from inter-departmental or team meetings dedicated to accounts sometimes went unrecorded. Unfortunately, there was no standard format to record this detail, except perhaps the oft-overlooked comments fields.

Using software to align teams

Nowadays, a choice of feature-rich software packages has made the latest in Artificial Intelligence (AI) available to the world of pharmaceuticals. Now, it is possible to manage information, answer queries and display reports with ease.

Such packages typically boast intuitive and user-driven interfaces to acquire and preserve essential details. Also, powerful algorithms search for connections, log the results and analyze
implicit knowledge such as key stakeholders and their links.

Group knowledge becomes implicit by asking brand teams to share data about accounts via influence maps. Later, colleagues and members of other groups can leverage this information in a productive, cross-team approach.

Across the pharma manufacturing sector, cross-functional teams can now benefit from granular and accurate account stakeholder maps, updated in real-time. Significantly, team alignment and influence maps allow pharmaceutical companies to get the most from their team's relationships with each corporate function and - crucially - with stakeholders.

The benefits of software automation include:

• Increased efficiency and little or no duplication.
• Coordinated actions and enhanced accountability.
• Helps pharma companies to prioritize the most significant relationships and develop a stakeholder influence map, measured using validated benchmarks.
• Enables overviews of multiple accounts and relationships between critical stakeholders by zooming out to regional and national levels.
• Identifies connections between health care providers and teams, enabling rapid reference and access.
• Records memorized account knowledge in a secure database.
• Characteristically, available off the shelf as ready-to-go systems.
• Easy to populate with publicly visible connections and salient information on stakeholder connections.
• Promotes a paperless office environment.

Making influence maps work for you

An AI based engines will identify Key Opinion Leaders (KOLs) based on the accumulated data. Pharmaceutical companies have used the influence of highly experienced researchers and physicians to seek out more takers of new drugs and clinical trials. Artificial Intelligence can add more value by quantifying their influence and giving back an elaborate measurement to run a better campaign. Pharma companies can implement Machine Learning for allocating right experts for campaign needs via influencer marketing. For this, AI can be fed number of topics, publications, research produced by such experts and understand their audience.

So, there you have it. If you are a business decision-maker or policymaker, you now have an exciting opportunity. Deployed to good effect, the latest influence mapping techniques and AI look set to fuel organic business growth in forward-thinking pharma companies.

Cloud computing can offer businesses many benefits. Most companies use cloud computing to set up virtual offices that can be accessed from anywhere in the world. Cloud computing can make communication and coordination between employees seamless. The technology behind the Cloud is constantly improving, with innovations being introduced each year. With that said, if your business still hasn't adopted the technology, consider the following reasons why you should.

The Cloud can help save on expenses

Businesses often hesitate to adapt to new technologies because of cost concerns. But the thing about cloud hosting is that you don't need to spend too much on hardware if you want to adopt it. Space, power, air-conditioning, maintenance, and insurance costs aren't things that you have to worry about because your provider's servers will handle most of the heavy lifting for you. More importantly, most cloud services have very flexible plans, allowing you to only pay for services that you absolutely need.

You can also reduce IT costs if you're working with the Cloud. You won't need to pay for new hardware or software when upgrading your system because your provider will do that for you. You won't need to hire as much IT support staff because your provider will cater to your needs. More importantly, you won't need to pay for as much power because you won't be managing your servers.

Scalability is a built-in feature

Scaling up your business costs money. Without the Cloud, you'll need to purchase hardware, floor space, and spend more on power if you want to scale up your servers. However, Cloud brings scalability to the game. Typically, if you receive a boost in website traffic, you'll need to purchase new servers. But if you're working with a cloud service provider, you might only need to update your plan. Alternatively, you can also subscribe to a pay-as-you-go payment scheme, wherein you only pay for resources that you need. Going down this route means that you won't need to pay for a package permanently and will only need to pay your provider based on your exact needs. Flexibility and scalability are two things to expect when working with the Cloud.

Cloud-based services are blazing fast

To stay relevant, a cloud service provider adapts to the latest tech. Service providers always make sure that performance is optimized. Because of this, expect providers to take advantage of the latest CPUs, SSDs, and hardware. With so much tech at their disposal, working with any cloud service provider is guaranteed to be a lightning-fast experience. Accessing your files and working on the Cloud should be a seamless, lag- free experience.

The Cloud is highly secure

Many organizations are concerned that the Cloud isn't secure. If files are accessible from anywhere in the world, what is the guarantee that they're being appropriately protected? The truth is cloud service providers place a significant emphasis on security. Cloud hosts carefully monitor their safety, and in most cases, they are more secure than traditional, in-house systems. Data is often encrypted, and things like two-factor authentication can make data theft more difficult for would-be hackers.

Collaborating on projects will be easier

The Cloud allows members of a company to coordinate over vast distances instantly. This is one of the main reasons why companies invest in cloud-based services. The benefit of working on a worksheet together with someone from across the world is well worth the cost. Grant contractors and other third party’s access to relevant files or records with the click of a button can lead to a ton of productivity. Working with the Cloud can provide your business with various benefits at an affordable cost. Take note of the advantages mentioned in the article and consider investing in the Cloud.

Since the transition to hybrid and remote work models began in earnest in 2020, cybercriminals have ramped up their efforts to exploit weaknesses and new vulnerabilities associated with these distributed environments. Surveys and studies have shown that remote workers are often taking shortcuts that circumvent security policies. More than ever, personal devices that may not be configured to meet security requirements are being connected to company resources. Home offices are essentially beyond the control of employers; thus, physical access controls are virtually non-existent. These are a few of the issues companies are struggling with as they strive to provide secure and dependable remote access to their staffers and monitor their work-related activities. Although it was developed before the 2020 workforce transition, the Secure Access Service Edge (SASE) concept seems tailor-made for today's iteration of the wide-area network.

What is SASE?

The cloud-based SASE service model combines wide area network (WAN) capabilities with security tools including Firewall as a Service (FwaaS), Cloud Access Security Broker (CASB), and zero trust access controls that will address and resolve many issues associated with hybrid and remote workforce environments. SASE facilitates secure connections to resources regardless of where they are in relation to those who need access to them. User access controls are based on identity, location, access timeframes, and user device risk assessments. By using what is known as worldwide points of presence, SASE reduces or eliminates latency across what can be a global network.

Zero trust is a critical component of SASE. Traditionally, everything and every user within a secured network is afforded at least some level of trust. For example, a user can move about a network accessing resources based on permissions assigned to their account once logged in. However, zero trust emphasizes on "never trust, always verify" principle. Rather than a user signing in once and having the ability to move laterally around the network during that session, both the user and device being used in a zero-trust environment would be required to authenticate each time they attempted to access designated "micro-perimeters" within the network. These micro-perimeters could be encasing applications or services, data, or other assets. Zero trust controls grant access to a micro-perimeter by verifying user identities, devices, request types, locations, activity history, and timestamps. Should a bad actor manage to gain access to a network protected by zero trust controls, they would likely find it impossible to move about and access critical resources.

SASE is highly scalable and flexible. Among others, available security features of SASE may also include data loss prevention, sandboxing, DNS security, and web filtering. Because it is cloud-based, SASE can reduce costs associated with procuring, managing, and maintaining technology resources.

Remote work with SASE

The SASE components discussed thus far serve as examples of how they can benefit organizations whether they are utilizing hybrid, remote, or more traditional work models. There are, however, some SASE advantages that relate more directly to securing and managing remote employees.

SASE facilitates better control over which remote staffers can access applications and websites. It provides more visibility into their access and usage of company resources, thus allowing management to better track those working without direct supervision and ensure that they adhere to policies. The access controls offered by SASE help to lock down home offices by blocking access via unauthorized devices. They prevent the exfiltration of sensitive data and ensure that the absence of organizational control over the physical security of the home office environment does not result in company assets falling into the hands of unauthorized individuals. Additionally, remote workers will connect to company resources via a zero-trust network, thus preventing those resources from being exposed to Internet-based threats.

In closing

Cybercriminals are increasingly targeting remote employees. New threat vectors seem to emerge daily. Remote location and hybrid work models have now become the standard. The recent Covid-19 pandemic is driving an entirely new model of working. SASE not only addresses the threats via its suite of security controls, but it also provides employers with greater insight into and control over the activities of their remote staffers. SASE dramatically reduces the vulnerabilities associated with maintaining a non-traditional WAN that includes numerous sites in the form of home offices where management lacks control over physical access.

While the transition to SASE takes time, especially for an organization currently maintaining its own IT infrastructure, the long-term benefits make it worth the effort, and they may include cost savings as well.

By Nikhil Shintre

Over the last decade or so, cloud has evolved as a preferred IT deployment model. Popularity of cloud can be gauged from the fact that majority of the enterprise IT providers are now having some kind of cloud offering, and most of the startup launched in this period are cloud native.

As cloud adoption becomes common practice and the benefits are well established, a larger number of enterprises move their current application stacks to cloud. As part of this shift, they also expect the Independent Software Vendors (ISVs) to enable and optimize their software for cloud. However, for the ISVs this require much deeper considerations like commercial models for cloud enablement, acceptance by the existing customers and the impact on acquisition / onboarding of new customers.

Models for Cloud Enablement -

From our experience, we see three possible models for cloud enablement – Cloud enablement in customer setup, Cloud enablement with the setup managed by ISV, and a full fledge multi-tenant SaaS setup managed by ISV.

• Hosted in Customer Cloud – This is for customers who prefer to deploy the software in their own cloud setup, by applying their own security controls for the software and data.From the ISV perspective, this is easiest to implement by adopting certain services like scaling, storage and monitoring in the software. However, since each customer could have their own cloud preference, it is advisable not to commit too much to a specific cloud service.
• Single Tenant SaaS – In this model, the ISVs deploy per customer isolated application stack either in a common cloud account or a dedicated account controlled by ISV. Both modes isolate customer specific stack, to address the concerns about security.In this model ISV handles complete deployment, monitoring and maintenance. This gives ISV flexibility to choose the cloud provider and plan the cloud enablement and optimization.
• Multi-Tenant SaaS – In this model, the ISVs deploys a single application stack with customers separated via multi-tenant implementation at the application business logic and the database level.This requires major restructuring of the application to ensure software level separation of tenant specific data and user access. Since this is software level separation, it needs to be carefully maintained during the development.
• This model aggregates the usage of resources to the best possible manner and gives the ISV the flexibility to choose the cloud provider and various services.

Comparing the Enablement Models -

Each of the above three models has its pros and cons in terms of effort for cloud enablement, maintenance of the setup, and licensing / pricing. These aspects can be compared as below.

How to Choose Between the Models –

Each of the three models serve a particular situation, but it is difficult to define specific rules around it. Instead, as a general guideline following aspects can be considered -

• Large customers would like to manage the application as per their security practices. Hence, if majority of customers are large sized, software hosted in customer cloud would be preferred.
• If the application is very critical in customer’s business process, the customer would prefer to control the data. For such applications, software hosted in customer cloud would be preferred.
• Application having tighter integrations with other enterprise systems, are difficult to move out from the customer. In such case, software hosted in customer cloud would be preferred.
• If the application has many small customers, or there is large no of users with small time of usage, multi-tenant SaaS is a win-win model for the customer as well as ISV.
• If the application requires continuous addition of features (e.g. New Product Development), multi-tenant SaaS makes it easier for faster deployment and fine-tuning.
• If the application involves data aggregation and data based inferences (viz AI/ML based), multi-tenant SaaS makes it easier to manage it at one place.
• When customer insists on a more stringent separation, but wants all other benefits of SaaS the single tenant SaaS can be chosen.

As a final word, the cloud enablement model must ensure smooth transition for existing customers, and ease of acquiring / onboarding new customers. So it is important to involve the product management, engineering and the customer support functions in any decision.

References –

https://docs.microsoft.com/en-us/azure/azure-sql/database/saas-tenancy-app-design-patterns

https://aws.amazon.com/blogs/apn/architecting-successful-saas-understanding-cloud-based-software-as-a-service-models/

https://cloud.google.com/kubernetes-engine/docs/best-practices/enterprise-multitenancy

IT software outsourcing and CAD software outsourcing are some of the largest industries in the 21st century. Software development outsourcing takes place for various reasons, ranging from requiring specialized software/professionals to creating a digital product or addressing a given task.

A survey report indicates 57% of US start-ups have already outsourced their software development process.

Regardless of cases, outsourcing IT & CAD software projects is a positive decision that accelerates and accomplishes a software development need. But there is some caution to this.

Anything listed on the internet as software development service is not necessarily a perfect solution to your projects. There are various factors to look into, which makes finding a software development service an uphill task.

To make it easier for you, let us have a walk of some of the best and widely advised practices to adhere to when outsourcing software development projects. 

Conduct background check

The first step is to evaluate your requirements and look for various software development service providers. Prepare a list of candidates. It helps in assessing market costs for such services and allows you to fix a reference point. 

Once you have a fair idea, go ahead and shortlist the outsourcing firms that fit best to product requirements.

Carry out extensive research on the shortlisted companies and sort your preferred ones out. You should assess them based on their proficiencies, average turnaround time, and client reviews/testaments. Remember, you are entering into a relationship with a 3rd party vendor, and you cannot leap of faith. It is essential to be wary of anything that concerns your project and requirements. Starting a business partnership is easy but getting out of it can be messy if things go downhill.

Sort out your expenses in the correct order

There is a factor called Value for the product. The cheapest of things out there doesn’t necessarily mean they are your best bet. Even with a fixed budget, it is recommended to look for quality and not just the cheapest outsourcing vendor available. It would be best if you struck a balance between your expectations and your expenses.

Once this is figured out, the next step is to figure out the payment process and payments intervals. Businesses often come across situations that trigger payment hassles, so such possibilities must be considered and discussed beforehand. There is also a high chance of crossing the stipulated budget when outsourcing a project due to unforeseen necessities or unexpected circumstances. Therefore, it is best to leave some space in your budget for such circumstances. After all, better to be safe than sorry.

Choose the most suitable pricing model

The next step after arranging finances is looking into different types of pricing models. In this case, the pricing model is about the payment structure agreed with the vendor partner. Here are some commonly used pricing models:

• Hourly rates: In this case, a vendor is paid a fixed rate per hour. This model suits smaller software development projects since their lifecycle are short; hence, it makes sense to consider it hourly. This model also comes in handy when you have projects that only require minute modifications.
• Fixed rates: Fixed budgets involve an arrangement with clear and well-defined goals, scope, and timeline.
• Dedicatedy: Large projects or companies require a fully dedicated team, and such models need teams to work on-site. 

To find the best model that works for your project, sit down, and chalk up a plan of action with the 3rd party vendor partner.

Ensure tight security of your project and product

It is an important side many up-and-coming project owners might overlook. There are a few crucial security steps you should take to safeguard your product while dealing with third-party vendors:

• Enact a secure means of transferring information on the project.
• Implement a degree of access control over sensitive data.

Please enquire about the security measures and protocols the vendor partner has set up and how they plan to work with your data. Generally, a good NDA (Non-Disclosure Agreement) should sort this out. An NDA will clearly state the clauses regarding what is allowed and not allowed with the information once the vendor partner has possession.

Set Benchmarks

Although in the software development process, various working models have been put to the test. The agile methodology is popular among all. The reason for such a working principle is that a project without a definite aim and timeline can end up in a catastrophe. Some companies have witnessed such malfunctions since they put all their hopes upon the vendor team. It is vital to fix certain milestones and mini goals, to keep a step-by-step approach on the total lifecycle of the project. It also prevents the project from becoming a cluster, and you can monitor, and track completed and pending tasks. 

Proper documentation

Record keeping has been an essential aspect from biblical days. Proper documentation acts as a footprint of how your project has evolved through the whole process. The reasons why you should have adequate documentation is because:
• Documentation makes it easy to retrace procedures in case of any hassle pops up.
• Documentation maintains a written record of all transactions between you and the vendor partner.
• Documentation is one of the ways to ensure there is no room for mistakes and errors over scope, requirements, materials, content, or responsibilities.
• If you have a particular outsourcing or in-house team, good documentation is essential to understand the steps incorporated and helps following up on pending work. It makes upgrading and modifying a less cumbersome process.

Establish communication outlets and time schedules

One of the most significant issues while working with 3rd party vendor team is the lack of clarity regarding instructions and misunderstanding when developing custom applications. Such issues lead to delays and sometimes render incomplete or botched software. To address this matter, the first thing to do is set up a suitable communication medium right at the beginning of the project. The project scope and deliverables must be clearly explained and understood by both sides. During the operation, both teams should cooperate, and there must be periodic meetings on progress, issues, actionable, etc. A steady flow of information makes it easier for both parties to stay updated. If you are dealing with a foreign-based vendor partner from a different time zone, make sure the time constraints are considered, and there is no language barrier.

Set realistic goals

Finally, you must consider human factors. Dealing with humans requires flexibility. It is impractical to give a gigantic project to a vendor partner and set a short time frame expecting delivery by the deadline. You will end up with patched-up software that malfunctions. Remember to allocate time and resources for unexpected occurrences. Again, better to be safe than sorry.

An application may look impressive, but if it fails to perform as intended, your investment can be considered waste. When engaging with a 3rd party service, the emphasis should be on the desired functions, features, and smooth, easy user interface over aesthetics. Once your product performs as it should be, you can focus on its appearance and finishing look. This paragraph here no way rules out the importance of attractive looking, well-presented product, but more than what meets the eye.

Entering a partnership with a new 3rd party software development team is a meticulous and time-consuming process. However, keeping the points mentioned above should ensure seamless cooperation between you and the partner.

Software development outsourcing has been a common practice for quite some time. This business model has been adopted worldwide for many plus points, for example, tailored budgets, time savings, adding expertise, etc.

But anything with pros has its cons as well. You might have read about news headlines saying outsourcing is fading away; it is an old business model or how outsourcing can have negative consequences and outcomes.

Delegating IT services to 3rd party vendors is a universal cure for so many businesses. Things don't always go that as intended. The assurances of the desired result also include risks that can turn a seemingly decent idea into debris. Chief executives and Project Managers across companies have to brainstorm and develop technical challenges to stay on track with the ever-changing market ecosystem and consumer expectations. There are notable pain points concerning custom software development.

By now, you might be having second thoughts about outsourcing your IT project. But don't worry because although it is impossible to abolish all the negative factors associated with outsourcing, you can still put some anticipation and mitigation to work and bypass the issues. 

A 2016 survey about outsourcing software development projects has marked out some specific pain points. Basing on the survey, the following are some common concerns regarding outsourcing software development and ways to address them:

Quality of Service

One of project managers' most frequent and biggest frustrations is the poor quality of service while dealing with software outsourcing services. Budget-centric outsourcing firms tend to supply inexperienced and cheap-to-afford software engineers. This strategy filters out the more talented cream of the crop who charge a premium for their skills. Sometimes, even teams tailored as per high skillset also fail to meet the expectations despite extensive recommendations. Now check out how to address this issue in the below-mentioned tips.

Tip 1: Too cheap rates

In a bid to save expenditure, don't sabotage your product. Usually, the cheapest ones are the worst. After all, it is the value in exchange for money. Selecting the most inexpensive services might compromise the quality of a product. Surf through various software development rates and calculate an average to regard it as a reference point. 

Tip 2: Always ask for a free trial or opt for an MVP

Make sure you ask the 3rd party software service provider to demonstrate a free trial. It is done to judge code quality and their ability to meet the deadline.

There is another way, and it is known as a minimum viable product (MVP). MVP is invoked to test a business idea. Creating an MVP takes 3-4 weeks. MVP helps determine if the team meets your requirements — their update procedure, communication levels, time-zone constraints, and they have the necessary skills and expertise to get the job done.

Tip 3: Cite requirements in the contract agreement

Create an agreement document for the two parties. Define your quality requirements in the agreement. The agreement should mention coding standards, quality standards, criteria for the final product, the list of devices the product is supposed to work in, etc.

 There are occasions where products work decently at first but start giving errors and malfunction in the next couple of weeks when the vendor has delivered and is not responsible anymore. Therefore, to avoid such headaches, fix a warranty period by negotiating, during which the vendor development team will correct all the bugs for no added cost.

Extra expenditure

Outsourcing often leads to uncalled expenditures you may have never expected. It is a common phenomenon. You might end up seeking advice and help from a contract lawyer or business analyst. Maybe some added business trips.

However, it has been observed, the significant causes of extra expenditures in outsourcing are the following aspects:

• The client didn't clarify their requirements.
• The client suddenly wishes to add new features not mentioned in the agreement or make changes beyond the agreement's scope. 

Tip 1: Define your requirements and expectations clearly

When talking about large and complex and software projects, it is impossible to foresee every possible challenge and consider every detail. Throughout app development, requirements are often redefined, modified, and new features are added. If you clarify your needs at the starting phases, the cost estimate will be much more accurate.

Tip 2: Be prepared to pay extra if needed

Always be ready for minor changes that pop up during app development which can be implemented without using extra resources. However, if your project requires a previously unexpected new feature and you decide to enforce them, prepare a change request. These alterations influence schedule, scope, and budget will be revised and changed accordingly.

Tip 3: Create a clearcut legal document

Legal documents are pretty complicated to read since contracts or change requests must be as detailed as possible. However, the agreement has to be easy to read and understand. An agreement resembling a word salad with tricky legal jargon may not reveal the costs involved clearly. Carefully reading every clause and line before signing is a must.

Intellectual property issues

When you provide the outsourced team with confidential information, there's always a looming danger of information leakage. The outsourced partner might use your product or its elements as their own, or worse, give it to the next client. To overcome this, You should apply legal measures to protect your intellectual property.

Tip 1: Create a Non-disclosure agreement

An NDA is a legal method of protecting IP rights that specifies confidential information that requires serious privacy. NDA information encompasses business secrets, technical know-how, designs, ideas, customer lists, and other necessary information sent to the service provider. When the vendor signs the NDA, they agree not to exploit or reveal confidential information without prior client permission. In case of NDA violations, the agreement stipulates conditions of penalties and legal prosecution.

Tip 2: Include your final app in the agreement

The contract must specify the clauses mentioning the IP right regarding the final product, and all related aspects such as source code, algorithms, etc., must be transferred to the owner. To simply put, the product belongs to you after you've paid the bill.

Tip 3: Regard your service provider as your partner

One fact that could give you a sense of security is forging a long and trustworthy partnership with a well-grounded service provider. Once a business relationship matures and you start regarding each other as partners, the possibilities of IP rights infringement decrease. This mutual trust promises a sense of safety and utmost security.

The language barrier, Time zone differences & cultural fit

A thoroughly professional proficient English-speaking team is not easy to find. 3rd party services will give assurances about their team's proficiency in English, but it is not as accurate as they claim.

Time zone differences are a common and frequent facet of outsourcing software development, and occasionally, the outsourcing company sets the tone. But time zone differences also affect product delivery deadlines and seamless communication between teams.

Culturally fit is a significant pain point when hiring an offshore outsourcing vendor company. Too many cultural differences and diverse mindsets can lead to botched communication and drain your energy and resources.

Tip 1: Language focus as a criterion

Make sure your supposed service partner has a working environment that observes English as the working language, considering English is now the lingua franca. English language issues come up, especially when dealing with nations in South East Asia. In such cases, try conducting a one-on-one interview with prospects to know if you can understand each other.

Tip 2: Set a fixed time or Nearshoring

The best way to manage this is to know about the time zones of outsourced software developers and agree upon fixed online meeting hours. It has to be sorted out right when shortlisting possible vendor partners or even before signing the contract agreement. Nearshoring is another excellent choice since it presents lesser time zone differences.

Tip 3: Cultural compliance

A similar mindset is essential in business. Thus a more suitable outsourcing company would be the one that not only understands your work culture but culture as a whole.

Most of the risks mentioned above emerge when delegating a software project to a 3rd party developer team for the first time. A 3rd party service provider who can understand product requirements, client expectations, respect contracts, and IP rights, build a well-structured development team, and working model is a wish-cone-true. Being meticulous at the early stages will help you prevent mishaps and pain points. Also, it's about time you understand the importance of developing a partnership with your vendor.

By Pruthviraj Jadhav

Abstract

Artificial Intelligence is the talk of the tech town. The capabilities that AI can exhibit are breaking all sorts of boundaries. There are intelligent AI projects that can create a realistic image, and then there are ones that bring images to life. Some can mimic voices. The surveillance-based AI can predict the possible turn of events at a working space and even analyze the employees based on their recorded footage. (To learn more about smart surveillance, visit www.inetra.ai)

This blog talks about a generation of AI that can identify human behavior and are special ones.

We are talking about the Expressions Social and Emotion AI, a recent inductee in the computing literature. The Emotion AI incorporates the AI domains adept in automatic analysis and synthesis of human behavior, primarily focused on human-human and human-machine interactions.

A report on “opportunities and implications of AI” by the UK Government Office for Science states, “tasks that are difficult to automate will require social intelligence.”

The Oxford Martin Program on the Impacts of Future Technology states, “the next wave of computerization will work on overcoming the engineering bottlenecks pertaining to creative and social intelligence”

What is Emotion AI?

Detection and evaluation of human emotions with the help of artificial intelligence from sources like video (facial movements, physiological signals), audio (voice emotion AI), text (natural language and sentiments) is Emotion AI.

While humans can understand and read emotions more readily than machines, machines can quickly analyze large amounts of data and recognize its relation to stress or anger from voice. Machines can learn from the finite details on human faces that occur too quickly to understand.

The Brunswik Lens Model

Let’s have a look at Fig. 1 shown below. The person on the left is characterized by an inner state µS that is externalized through observable distal cues. The person on the right perceives these as proximal cues; stimulate the attribution of an inner state µP (the perceptual judgment) to the person on the left.

From a technological perspective, the following actions are possible –

• The recognition of the inner state (mapping distal cues into the inner state).
• The perception (the actual decision made by the decision-maker).
• The synthesis (the optimal or correct decision which should have been made in that situation)

Fig 1. The Brunswik Lens Model

The Brunswik Lens model is used to compute the human-human and human-machine interactions and their emotional aspects. It is a conceptual model with two states − the inner and outer state. The outer state is easily visible for the observer but not much conclusive. The inner state is not easily understandable but leaves some physical traits (behavior, language, and physiological changes) used to perceive the inner state (not always the correct one).

For example, a happy person might shed tears of joy, but another person will consider the former in grief.?

These physical traits can be converted into data suitable for computer processing and thus, find their place in AI. In addition to the above, the Brunswik Lens covers another aspect of Emotion AI: the capability to synthesize observable traits that activate the same attribution processes that occur when a human’s traits are displayed when perceived by a human observer.

For example, suppose an artificial face displays a fake smile. In that case, humans tend to believe that the machine is happy, even though emotional expression is impossible with artificial entities since they cannot experience it.

However, people can understand the difference between humans and machines at a higher level but not at a deeper level where some processes occur outside their consciousness. In other words, a human’s reaction to machines is like how they react to other humans. Therefore, human-human interaction is a prime source of investigation for the development of human-computer interaction.

How does Emotion AI work?

Emotion AI isn’t limited to voice. It uses the following analysis –

• Sentiment analysis is used to measure and detect the emotional data of text samples (small fragments or large samples). It is a natural language processing method & can be used in marketing, product review analysis, recommendation, finance, etc.
• Video signals - It includes facial expression analysis.
• Gait analysis and gleaning - Certain physiological signals through video are analyzed to learn about heart rate and respiration without any contact using cameras under ideal conditions.

Social Media giant ‘Facebook’ introduced the reactions feature to gain insights and data regarding user’s responses to various images.

Fig 2. Reactions feature on ‘Facebook.’

Emotion AI needs user-generated data such as videos or phone calls to evaluate & compare reactions to certain stimuli. Later, such large quantities of data can be morphed into human Emotion and behavioral recognizing patterns using machine learning. It can leverage more in detail emotional reactions users have with the help of the high computational capability of machines.

Oliver API

Oliver is an Application Programming Interface, also known as Oliver API, a set of programming frameworks to introduce Emotion AI in computer applications. Oliver API permits real-time and batch audio processing and has a wide array of various emotional and behavioral metrics. It can support large applications and comes with easy documentation. SDK is supported in various languages (javascript, python, java) and examples to help programmers understand its operation quickly.

The Oliver API Emotion AI can evaluate different modalities through which humans express emotions, such as voice tone, choice of words, engagement, accent. This data can be processed to produce responses and reactions to mimic empathy. The sole aim of Emotion AI is to provide users a human-like interaction.

Industry predictions -

• Global Emotion AI: According to ‘Tractica,’ the global Emotion AI market will grow from USD 123M in 2017 to USD 3,800M in 2025.
• Social Robotics: The revenues of the worldwide robotics industry were USD 28.3 billion in 2015 and are expected to reach USD 151.7 billion in 2022.
• Conversational Agents: The global market for Virtual Agents (including products like Amazon Alexa, Apple Siri, or Microsoft Cortana) will reach USD 3.6 billion by 2022.
• Global chatbot market: Valued at around USD 369.79 million in 2017 - is expected to reach approximately USD 2.16 billion in 2024.

Fig 3. Global Emotion Analytics Market (MRFR Analysis)

Applications -

• Medical diagnosis – In certain diseases which need an understanding of emotions like depression and dementia, voice analysis software can be beneficial.
• Education - Emotion AI-adapted education software with capabilities to understand a kid’s emotions and frustration levels will help change the complexity of tasks accordingly.
• Employee safety - Since employee safety solutions and their demands are on the rise, Emotion AI can aid in analyzing stress and anxiety levels.
• Health care - Emotion AI-enabled bot will help remind older patients about their medications and monitor their everyday well-being.
• Car safety – With the help of computer vision, the driver’s emotional state can be analyzed to generate alerts for safety and protection.
• The autonomous car, fraud detection, retail marketing, and many more.

Conclusion –

Emotions are a giveaway of who we are at any given moment. It impacts all facets of our intelligence and behavior at the individual and group levels. Emotion AI helps in understanding people and offers a new perspective to redefine traditional processes and products. In the coming future, it will boost up businesses and be a beneficial tool in medical, automobile, safety, and marketing domains. Thus, decoding emotions – the fundamental quality that makes us human and re-coding it to machines will be a boon to our future generation.

References –

1. https://www.aitrends.com/category/emotion-recognition/page/2/
2. Perepelkina O., Vinciarelli A. (2019), Social and Emotion AI: The Potential for Industry Impact, IEEE 8th International conference on ACIIW, Cambridge, United Kingdom.
3. https://oliver.readme.io/
4. https://www.acrwebsite.org/volumes/6224/volumes/v11/NA-11
5. https://mitsloan.mit.edu/ideas-made-to-matter/emotion-ai-explained
6. https://dmexco.com/stories/emotion-ai-the-artificial-emotional-intelligence/
7. Brunswik E. (1956), Perception and the representative design of psychological experiments, University of California Press.
8. https://www.marketresearchfuture.com/reports/emotion-analytics-market-5330