Explore the intersection of edge, AI and IoT

“Data is the new oil” has been on the radar of corporate CIOs for more than 15 years. Since then, enterprise data stacks have evolved to support complex business intelligence tasks. Most recently, in December 2022, we witnessed yet another tectonic shift thanks to Open AI’s ChatGPT.

When combined with the opportunities presented by these shifts, it is clear that machine learning (ML) and artificial intelligence (AI) have exponentially changed the data stack of enterprise IT and OT, while providing the opportunity for digital transformation. New tools. At the same time, we are witnessing the maturation of IT architectures and the adoption of edge technologies, leading to the bold claim that “the edge is covering the world!”

At the same time, computer vision and the Internet of Things (IoT) are combining to disrupt this pattern. This article will explore the opportunities and approaches at the intersection of these revolutionary market adoption paradigms.

Opportunities

A number of use cases and opportunities have been identified at the intersection of edge, AI and IoT, including:

•Preventive Maintenance:AI-based preventive maintenance, especially in manufacturing, is an important use case at the above intersection. According to the findings, the size of this opportunity exceeds $500 billion globally. In this context, AI’s ability to instantly process multimedia and detect anomalies at the edge to augment human decision-making is a critically relevant capability.

•Video Analysis:This involves using AI and ML to autonomously identify people/objects and their surroundings and make intelligent decisions. Some of these settings include smart cities, smart offices, smart retail stores, construction sites, and manufacturing environments. According to a McKinsey report, China's economy is expected to reach at least US$4 trillion by 2025.

•Other applicable areas:Includes autonomous systems, energy management, remote monitoring, telemetry and advanced driver assistance systems (lidar-based), as well as smart video and image recognition applications in healthcare .

While the potential market and economic size of this intersection is impressive, what is even more interesting is that China is expected to grow at a compound annual growth rate of nearly 30% by 2027.

Method

Any market shift and adoption paradigm goes through a maturity curve, during which various areas of friction are systematically addressed. The simultaneous nature of adoption and opportunity at the intersection of edge, AI, and IoT presents many areas where ecosystems can interact to create lasting value. These include:

• Edge Infrastructure: The need for shared passive data center infrastructure as well as active multi-tenant hardware infrastructure at the edge is well understood. And a new set of players is rising to the challenge, including tower companies and managed service providers.

•Reliable connectivity:The importance of ultra-reliable, low-latency connectivity cannot be underestimated given the multitude of platforms that need to co-exist at the edge. This is now a requirement of the 5G standard, and dedicated 5G-as-a-service API products are solving targeted challenges in this area. Additionally, given an API-first approach, enterprises can more quickly control and customize their connectivity needs.

• Edge data orchestration: This challenge is at the heart of the edge and AI overlay. It’s no secret that IT and OT teams are dealing with a deluge of data across all layers of the stack. In addition, using edge technology, you will face distributed orchestration issues. New edge-native data pipeline architectures are solving this challenge.

•Artificial Intelligence Model:With the emergence of generative artificial intelligence based on basic models, artificial intelligence methods applied to computer vision and the Internet of Things have opened up new lines of exploration and innovation. This is an active and dynamic solution.

• Programmability and Developer Ecosystem: The developer-first movement creates a vibrant economy brought about by a do-it-yourself approach and a consumption-based “as-a-service” model Better unit economics. Additionally, programmable edge APIs provide enterprise IT with multiple possibilities for control and customization across various ecosystem players.

While there are many challenges, many are being addressed simultaneously by a developer ecosystem that is achieving sustained and tangible results on all fronts.

Summary

New disruptive technologies at the intersection of artificial intelligence, edge technology, computer vision and the Internet of Things have brought a large number of market opportunities and also brought There are areas of friction that require new approaches. And edge programmable AI and edge-as-a-service market models, along with APIs and developer-first approaches, are starting to democratize the space. While these results are tangible, continued investment in innovation and a developer-first approach to collaboration is required.

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