Digital identity systems have evolved and continue to evolve. They are core to our interactions with the digital world and have made great strides in both security and convenience. However, the privacy and data-use consent of identity-holders remain problematic.

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What’s Inside

1. History of digital identity
2. Web 3.0 and a new digital identity
3. User & organization benefits
4. DID obstacles to adoption
5. Market and product outlook

History of digital identity

We have seen Digital Identity evolve from the silo identity model to the federated identity model. The current systems reside at a very low trust level, with over 93% of users distrusting social media platform’s digital custodianship. We believe the next stage of evolution will be Decentralized Identity

Web 3.0 and a new digital identity

Web 3.0, the internet’s next evolution aims for a decentralized interconnected and intelligent web. It aims for decentralized, peer-to-peer networks for secure, trustless transactions— without intermediaries. Unlike today’s static web that does not adapt to the needs of its users, Web 3.0 will be dynamic and interactive, leveraging AI and blockchain to personalize, adapt, and democratize the internet. As user identity is crucial in Web3, DID will be foundational. We explain the ecosystem and functionality of the DID network. Download Complete Research

User and organizational benefits

User benefits include credential forgery prevention, password-free authentication, spam prevention and many others. While Organizations will benefit from operational cost reduction and security cost reduction, enhanced user experience thereby improving the brand. Organizations must however use a phased approach to implement, which is explained.

DID obstacles to adoption

We identify four key obstacles that present themselves and what organizations can do to overcome them.

Market and product outlook

The global decentralized identity market was valued at $285 million in 2022 and is expected to grow at a CAGR of 88.7% over the next 5 years. We evaluate top players and products in the market and how they have helped the technology evolve. Download Complete Research

Credits
Author@lab45: Sujay Shivram, Abhigyan Malik

AIoT is a revolutionary blend of AI and IoT that creates a connected world with limitless opportunities. Smart devices can collaborate to make informed decisions without human intervention, transforming various industries. As AI and IoT converge, their applications will become more advanced, presenting new prospects for businesses and consumers.

What's inside

1. Insights and technology trends
2. Overview, benefits, and architecture
3. Use cases, challenges and key players
4. Enterprise AIoT adoption strategy

Insights and technology trends

1. AIoT enables devices to become smarter and more autonomous by analyzing massive data streams in real time and making informed decisions based on that data. They are expected to become more personalized and intuitive by implementing self-learning algorithms, providing real-time solutions. 
2. Fast, reliable connectivity ensures seamless user experience and data exchange, allowing AIoT systems to respond and act promptly.As cybersecurity technology advances, users gain confidence in the security of AIoT systems.
3. AIoT can contribute to sustainability initiatives through intelligent monitoring and control systems.
4. Integrating new technologies in AIoT systems has become an essential component in the future of enterprises and individuals. Key Technology Trends include:  Secure Access Service Edge (SASE), Nanotechnology, Multiplicity, Contextual Proactivity, Seamless Multi-Modal Interaction, Brain- Computer Interfaces.

Overview, benefits, and architecture

AIoT combines sensors, AI, data and ambient computing elements to create a responsive, context-aware environment. It uses embedded devices and natural user interfaces to provide services based on detected requirements and user input.

AIoT can revolutionize how users interact with technology, offering greater convenience and seamless connectivity. The benefits include: intuitive and seamless experience without commands, automated decision making, efficiency and convenience.

While creating an AIoT system, a well-balanced architecture is crucial to manage data processing speed and costs. There is a flow of information in the system based on the external inputs, that ultimately results in a response based on analysed data points by AI and ML algorithms. Download Complete Research

AIoT adoption – Connected enterprise strategy

The 5 step enterprise strategy include the following:

1. Define AIoT Vision, scope, goals and objectives
2. Assess IoT Capability, identify AIoT devices & systems
3. Define Connected enterprise System Architecture
4. AIoT System Development & Pilot implementation
5. Enterprise - wide implementation

Use cases, challenges and key players

Use Cases for following domains are discussed:

• Manufacturing: Employee safety, Inventory management, Collaborative robots (Cobots), AI-driven product design
• Smart Homes: Home Security, Health and Wellness, Child and Elderly Care, Home Automation
• Healthcare: Predictive Healthcare, Smart Wearables
• Automobile: Autonomous Vehicles, Smart Traffic Management, Connected Car Services
• Retail: Smart Shelves, Customer Experience, Ambient Commerce
• BFSI: Fraud Detection, Personalized Financial Services

Implementing a complex system like AIoT requires careful planning, collaboration, and attention to detail. Data management, privacy concerns, and integration with various systems can pose significant obstacles to successful implementation.

The AIoT space is dominated by key players such as IBM, Microsoft, Siemens, GE, Cisco, Huawei, ABB, Bosch, SAP, and Honeywell. Download Complete Research

Credits
Author@lab45: Anju James
Contributing Authors@lab45: Hussain S Nayak, Nagendra Singh

Manufacturing is becoming more smarter, efficient, precise, and sustainable by adopting IIoT, AI, Robots, Blockchain, and 5G for operations optimization. Manufacturing business trends are enabling flexible & transparent supply chains, customer-centric & agile production, ecosystem collaborations, and new business models.

What's inside

1. Key Takeaways
2. Key drivers shaping trends in manufacturing
3. Business Trends driving innovation
4. Technology Trends aiding the business

Key takeaways

The convergence of advanced technologies with labour, supply chain, and demand challenges is driving full automation. Nearly 84% of manufacturers have adopted or are considering smart manufacturing. Manufacturers are exploring tech-enabled ecosystem partnerships, reshoring, and factory-in-a-box model to address supply chain instability. AI, IIoT, Big Data & Analytics, Robotics, 5G & Edge Computing are enabling data collection, pattern identification, and prediction for process optimization and efficiency improvement. AI in manufacturing is expected to reach $115 billion in 2032 globally. Blockchain is ensuring supply chain and ecosystem security. Driven by regulations and environmental commitments, manufacturers are adopting technologies to reduce emissions. On-demand production, mass customization, and subscription-based products are enhancing customer experience. Download Complete Research

Key drivers shaping trends in Manufacturing

• Ensuring supply chain resilience and navigating market demand uncertainty are manufacturers’ main requirements amid natural disasters and geopolitical tensions. AI and Data Analytics are key to overcoming disruptions and predicting demand.
• Manufacturers are prioritizing automation to deal with skilled labour shortage, manage rising costs and enhance efficiency while maintaining quality.
• Sustainability is another priority for manufacturers, focusing on responsible materials sourcing, environment-friendly production, and safe waste disposal. Customer preference is changing, and they are seeking sustainable products and processes.

Business trends driving innovation

• Dark factories fully orchestrate processes using automated machines while operators remotely monitor activities, enhancing performance and resource efficiency.
• The product-as-a-service business model opens new revenue streams for manufacturers while lowering the upfront costs for customers.
• Global data exchanges & platforms allow data sharing between ecosystem partners while protecting proprietary data.
• Green manufacturing is getting propelled using digital technologies and adopting sustainability policies.
• Reshoring and micro-factories have gathered pace due to wage increases, supply chain disruptions, and the advent of digital technologies.
• Prescriptive maintenance identifies patterns, performs root-cause analysis, and recommends the best maintenance approach, lowering running costs and downtime.
• Customized product manufacturing is being enabled by additive manufacturing and flexible manufacturing approaches.
• Advanced environment-friendly materials are gaining traction resulting in enhanced performance, high wear resistance, and high thermal stability of products.
• These trends impact various stakeholders, including manufacturers, suppliers, workers, and customers.

Technology trends aiding the business

• AI is transforming manufacturing through real-time machine operation optimization, problem prediction, demand forecasting, cost modelling, product quality inspection, robot navigation, etc.
• IIoT is key for prescriptive maintenance, real-time production and machine monitoring. 5G provides high bandwidth for reliable connectivity between IIoT devices, offloading computation-heavy tasks to edge infrastructure.
• Robots & Cobots enable production line process handling, intelligent material handling, and warehouse automation.
• Digital Twin enables the convergence of information technology (IT), operational technology (OT), & engineering technology (ET) in manufacturing.
• Blockchain allows for tracking materials & goods through the supply chain, inventory management, & warranty management.
• Secure and dedicated private networks, Blockchain, and AI are increasingly used to safeguard critical manufacturing operations from cyberattacks.

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Credits
Lead Authors@lab45: Parag Arora
Contributing Authors@lab45: Hussain S Nayak