The Internet of Things (IoT) is changing how industries do business and promises a significant return on investment (ROI) in operational efficiency, improved customer experience, risk mitigation, and enabling entirely new business models. Further, with increasing global economic and regulatory pressures there is growing demand for IoT solutions to address these challenges. Many IoT projects start with the need to gain better visibility into a process, but Artificial Intelligence (AI) and Machine Learning (ML) within IoT create new opportunities to further enhance insights and in certain cases automate decision-making. Although the notion of computing based on data collected from things was not born yesterday, the meteoric rise of IoT has recently made it practical because of smaller, faster, cost-effective computing, increased connectivity, and increased storage density. Devices can now store, manage, and analyze vast amounts of information across billions of distributed devices in real-time. Incorporating AI and ML into the IoT equation is a game-changer.
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Table of Contents
- Overview
- The Shift To Decentralization
- A Layered Approach For Successful IoT Enablement
- One Size Does Not Fit All
- Something For Everyone
- Use Cases: Driving IoT Value And Innovation
- Conclusion
Companies Cited
- Dell EMC
- Dell Technologies
- EdgeX Foundry
- IMS Evolve
- Linux Foundation
- Pivotal
- RSA
- SecureWorks
- Virtustream
- VMware