Wednesday, March 22, 2023

The Convergence of Edge Computing and Cognitive AI

By Prangya Pandab - August 13, 2021 6 Mins Read

The Convergence of Edge Computing and Cognitive AI

The widespread disruptions of AI, ML, and IoT have caused considerable mind share across all industry categories. The growing trends of these innovative technologies are frequently complementary to one another, accelerating digital transformation and providing unique research opportunities.

Businesses across the word expected the past 18 months to bring pressure from the continuing trade tensions, the fallout of Brexit, automotive-industry issues, and declining demand. But no one expected the COVID-19 pandemic to plunge the global economy, as well as their own operations, into chaos.

It’s becoming increasingly evident how industrial artificial intelligence (AI) is truly empowering IoT implementation as the digital transformation of industry progresses and the tools, technologies, and methodologies that fuel change become more generally recognised.

Industrial IoT deployments have been disrupted by the proliferation of System-on-Chip (SOC), high-speed cellular (LTE/ 5G), fog computing, and long-range wireless networks. Intelligent Edge devices are gaining appeal as a way to reduce latency, network and storage costs, and provide reliable real-time operations while maintaining privacy.

New York based Ranial Systems is a platform engineering firm specializing in real-time process automation through the convergence of cognitive AI and Edge computing runtime. Edge native platform CognitIoT is their newest solution in the innovative tech field.

Also Read: IoT and Edge Computing Will Increase with 5G Adoption

“Our vision is to accelerate cognitive IoT solutions that address emerging challenges with climate changes and sustainability, mass adoption of EV and Renewable energy, cybersecurity threats on critical infrastructure, intelligent manufacturing, and connected health ecosystem,” says Prasenjit Bhadra, CEO, and Founder at Ranial Systems.

CognitIoT’s innovative embedded AI/ML services react to the changing operating environment, unlike the most typical edge-enabled IoT platform. The runtime can be provisioned for automated monitoring and control operations with minimal customization or configuration of the service components.

“Over the past two decades, the leadership team of Ranial has made a significant contribution in building first-generation IoT products using RFID, actuators, sensors, and mobile/ wireless technologies.”

“In light of extensive experiences at the global scale, the team is committed to deliver the untapped potential of Cognitive IoT in Industry 4.0 era by offering a full-stack (software + hardware) edge computing platform with intelligent process automation and peer-to-peer collaboration” he adds.

Distributed intelligence on edge

In the global context of distributed IoT implementation CognitIoT removes the overheads of operational costs and performance bottlenecks inside IoT networks and huge data center/cloud architecture designed for ‘remote-only monitoring and control activities’. Real-time anomaly identification, context-aware operation management, and actionable insights at the point of action are all made easier with distributed intelligence on the edge.

With intelligent control capabilities, the invention aims to deliver on-demand services that minimize downtime, achieve autonomy, and prevent security concerns. Ranial is constantly seeking to disrupt innovation in IoT and AI across the digital value chain in a world of limitless possibilities.

Also Read: Overcoming Barriers to Edge Computing Adoption and Deployment

Ranial is the only Industrial IoT platform to bring cognitive AI and real-time intelligence to the point of action. Ranial has created an integrated hardware and software runtime that can diffuse prescriptive and predictive intelligence at the network’s edge by utilizing high-performance industrial compute modules (SOC, SBC).

CognitIoT’s innovative embedded AI/ML services adapt to the changing operating environment, unlike the typical edge-enabled IoT platform. The runtime can be provisioned for control operations and automated monitoring with minimal customization or configuration of the service components.

The disruptive innovation

The disruptive invention, which is based on cognitive neuroscience models, provides considerable gains in incremental operational intelligence, autonomic functions and real-time monitoring. Edge computing is spreading into industrial IoT application domains to overcome the limitations of centralized computing but the limited hardware resources and data available on edge nodes make sophisticated AI/ML models impossible to execute.

By incorporating Cognitive AI capabilities, the invention bridges the gap between centralized and linear IoT architecture patterns and enhances distributed edge computing even further. Ranial’s disruptive invention reduces reliance on distant cloud runtime. The Intelligent Service components are designed to work in a restricted hardware environment and introduce semantic learning with incremental data, as well as create reasoning through interactions in the connected environment.

The proposed runtime adapts to changing cyber-physical environments, increases situational awareness, protects against cybersecurity threats, reduces the incremental cost of scaling network and cloud infrastructure, and provides extreme responsiveness in mission-critical M2M/IoT ecosystems like smart grid surveillance, remote patient monitoring, autonomous vehicles, defence weaponry systems, and so on.

How CognitIoT disrupts the existing market

Edge computing’s extensive adoption has resulted in a plethora of service opportunities and real-time use-cases that are closer to the operating environment. Predictive maintenance, condition-based monitoring, and other asset management due diligence are typically performed offline. Exception detection and system-level procedures are based on specified rules and necessitate human interaction.

Most AI/ML models fail to give quality insights with limited data and compute capabilities when deployed on edge nodes. Prasenjit says, “Our patented technology has crushed the strong partition between the hardware and software-centric functions to extend real-time IoT runtime. The unique design overcomes the limitation of edge computing and traditional IoT implementations. Translating information into actionable insight in a timely fashion and, gaining autonomy to automate complex functions are the key differentiators Ranial has introduced.”

Also Read: Digital Transformation and Edge Computing go Hand in Hand

To overcome the restrictions of limited resources and incorporate structured intelligence, Ranial’s innovation focuses on peer-to-peer collaboration among edge nodes. The pre-operatory cognitive models’ self-learning capabilities are meant to support interoperability, extreme scalability, automated control, and extension with minimal customization at deployment time. As a result, the analytical and execution models present a responsive decision support system on the edge that can adapt to ever-changing physical conditions while also preventing cybersecurity assaults by identifying abnormalities of any intrusive actions/requests

In their current state of engagement, Ranial now provides co-innovation services to mainstream engineering firms, cleantech companies, and OEMs with the innovations being accelerated through their digital platform. The company is also expanding its collaboration channels to include cloud solution providers and industrial automation firms that can deliver distinct differentiators by combining their technologies to enable real-time operational intelligence.

The Road ahead

“Our platform offerings are tagged to industry-specific solutions that have immediate and critical demand for cognitive operations. We have demonstrated the power of intelligence that can significantly lower the cost of operations, minimize downtime and catastrophic failures. Our strategic focus on compelling use cases would set references for intelligent IIoT implementation that would carry forward the innovation in intelligent edge computing and complex design of edge-to-edge collaboration across the value chain”, concludes Prasenjit.

Prasenjit Bhadra (Jeet) is a seasoned entrepreneur and tech evangelist who has made a significant contribution to the innovation and platform engineering of the enterprise-scale M2M/ IoT and AI space. He is the Founder and CEO of Ranial Systems, a US-based start-up initiative focusing on Cognitive IOT platforms to implement automated operations and asset management functions in smart Grid surveillance, Micro Grid/ Renewable integration, Advance manufacturing, and industrial Asset management space.

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Prangya Pandab

Prangya Pandab is an Associate Editor with OnDot Media. She is a seasoned journalist with almost seven years of experience in the business news sector. Before joining ODM, she was a journalist with CNBC-TV18 for four years. She also had a brief stint with an infrastructure finance company working for their communications and branding vertical.

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