Prasenjit Bhadra: Accelerating Cognitive IoT Solutions with Automated Monitoring through Ranial Systems
Ranial Systems is known as the leading IoT solution provider that converges cognitive AI and edge computing runtime. It is also a market leader in next-generation M2M/IoT platforms and solutions allowing real-time operational intelligence. The target audiences of Ranial are smart utilities, smart city, industrial, manufacturing asset management, remote patient monitoring, and connected health.
This is an interview of Prasenjit Bhadra, Founder, and CEO of Ranial Systems who has enlightened the readers on how he is focused on driving unique cognitive IoT solutions despite all kinds of hurdles on the way to global success. Prasenjit is known for possessing a clear perspective on emerging technology strategies and delivering unique proposals through Digital transformation. He is extremely knowledgeable and has successfully put together solutions with relentless effort.
Leadership in First-Generation IoT Products
With a headquarter in Forest Hills, New York, Ranial Systems is established as an Industrial IoT (IIoT) platform engineering firm that specializes in real-time process automation by converging the cognitive AI and Edge computing runtime. The patent design of the edge native platform is branded as CognitIoT. Unlike the most common edge-enabled IoT platforms, the unique embedded AI/ ML services of CognitIoT adapt to the changing operational environment. With minimum customization and/or configuration of the service components, the runtime can be provisioned for automated monitoring and control activities. The offering can be deployed as a SaaS (Software-as-a-Service) or dedicated on-premises instance as per the preference of clients. The vision is to accelerate cognitive IoT solutions that address emerging challenges with climate changes and sustainability, mass adoption of EV and renewable energy, prevent cybersecurity threats on critical infrastructure, intelligent manufacturing, and connected health ecosystem.
“Our team has led major digital transformation programs and co-innovation initiatives in RFID, Enterprise Mobility, Sensors and Actuators in last two decades. We envision in elevating IoT systems from a data collection engine to an informed real-time decision support system” said Prasenjit Bhadra, the CEO, and Founder of RanialSystems.In light of extensive experiences at the global scale, the team is committed to delivering the untapped potential of Cognitive IoT in Industry 4.0 era by offering a full-stack (hardware+software) edge computing platform with peer-to-peer collaboration and Intelligent Process Automation (IPA). Considering the global context of distributed IoT implementation, CognitIoTeliminates the overheads of operating cost and performance bottlenecks within IoT networks and massive data center/ cloud infrastructure designed for remote-only monitoring and control functions. The distributed intelligence on edge facilitates context-aware operation management, real-time anomaly detection and delivers actionable insights at the point of action. The innovation is targeted to deploy on-demand services that minimize downtime, gain autonomy and prevent security threats with intelligent control capabilities. In the world of endless opportunities, Ranial is always striving for disrupting innovation in IoT and AI across the digital value chain.
Designing an Integrated Platform with Inspiration
Ranial is the only Industrial IoT platform company to bring cognitive AI and real-time intelligence at the point of action. By taking advantage of high-performance industrial compute modules (SOC and SBC) Ranial has designed an integrated hardware and software runtime that can diffuse predictive and prescriptive intelligence at the edge of the network. Inspired by the cognitive neuroscience models, the optimized offers a significant gain in incremental operational intelligence, real-time monitoring, and autonomic functions. As edge computing proliferates into Industrial IoT application domains to overcome the limitation of centralized computing (latency, bandwidth, and single point of failure), the constrained hardware (compute and storage) resources and data available on the edge nodes fail to execute sophisticated AI/ML models. The unique IP of cognitive IoT runtime extends to— a unique set of embedded cognitive AI algorithms that eliminate the constraints of compute-heavy AI and establishing horizontal (edge-edge) as well as need-based vertical (edge-cloud-edge) collaboration across the connected nodes. These help to achieve high-performance parallelism to exchange real-time events or knowledge interchange and integrated workflows close to the point of action. The invention closes the existing gap of centralized and linear IoT design patterns and advances the distributed edge computing further by introducing Cognitive AI capabilities. The unique design of the IIoT infrastructure and architecture simulates the human nervous system’s anatomical layers that are responsible for sensing, processing, and responding through systematic coordination of neuro-motor operations. The disruptive innovation minimizes dependency on the distant cloud runtime. The intelligent service components are optimized to run within a constrained hardware environment and introduce semantic learning with incremental data and develop reasoning through interactions within the connected environment.
Tech Evangelist with Eminent Contributions
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, microgrid/ renewable integration, advanced manufacturing, and industrial asset management space. Prasenjit owns global patents, research publications, and articles in the large-scale distributed architecture of IoT and wireless solutions that converge the power of real-time cognitive AI with embedded systems and high-performance computing. The mission of the industry-focused R&D at Ranial systems is to drive inventions in advanced edge computing and real-time process intelligence that address emerging challenges of large-scale green initiatives and renewable infrastructure deployment, intelligent asset management, and cybersecurity threats. As the only global company offering Cognitive IoT solutions to industrial clients, Ranial is committed to driving continuous improvement in maximizing ROI, KPI, interoperability, self-healing, minimize downtime, and catastrophic failures using incremental learning and actionable insights. Prasenjit has served global leadership positions in tech giants viz. IBM, Wipro, Visa, UHG, and Broadridge to drive innovation and thought leadership in digital transformation initiatives. He has played key roles in driving enterprise architectural initiatives in the emerging technology space in the last two decades. He has led start-up initiatives in unique cloud-enabled platforms(SaaS) leveraging human-machine collaborations. Under his able leadership, the global IT firms partnered with fortune 100 clients in the adoption and modernization strategies of emerging technologies, OT/ IT convergence, and SOA best practices.
Prasenjit has contributed to open-source technologies, industry-specific assets/frameworks, and platforms. He has managed large global engagements, strategic business planning for budget allocation and fund-raising initiatives and, exposed to Global IT practices and business cultures across three continents (US, EMEA & AP). As a Senior Executive in medium to large corporations, Prasenjit has strategized, led the technology center of excellence in enterprise mobility, advanced analytics, and wireless space. He played a major role in rolling out innovative products in renewable asset management infrastructure, WIP tracking, and Enterprise middleware serving global clients and IT organizations for over a decade.
Prasenjit is awarded as CTO of the year by Corporate America, New York, and best CEO leading Business transformation by TMT News, UK. He is a senior member of IEEE and Sigma Xi. He is serving various global leadership and non-profit organizations like Top Tier Impact, Society of Risk Analysis, Association of Computing Machinery, etc. to promote R&D and innovation in sustainability and emerging technologies.
Adopting Technologies for Emerging Trends
The proposed runtime adapts to the changing cyber-physical environment, extend situational awareness, protect against cybersecurity threats, minimize the incremental cost of scaling network and cloud infrastructure and deliver extreme responsiveness within mission-critical M2M/IoT ecosystem such as smart grid surveillance, remote patient monitoring, autonomous vehicles, defense weaponry systems, etc.
The widespread adaption of edge computing has created ample service opportunities and real-time use cases closer to the operating environment. The most common functions of condition-based monitoring, predictive maintenance, and similar asset management due diligence are usually performed in an offline mode. The process of identifying exceptions and system-level operations is based on predefined rules and demand human interventions. Rapid adaption of renewable infrastructure, electric vehicles, and smart city ecosystems are demanding intelligent surveillance as well as autonomous operations. The disruptive trends of operational intelligence and real-time collaboration across the cyber-physical assets in the industrial domain are inheriting intuitive process automation. Such emerging trends are introducing purpose-based hardware and software layers with bespoke service components. Such silos designed with centralized IoT solutional architectures are exponentially increasing time-to-value and cost of ownership over time. Moreover, predefined rule-based logic and structured intelligence on edge nodes fail to deliver scalability, autonomy, interoperability, and intelligent control operations. The expansion in distributed IoT infrastructure is exposing an increasing number of channels for intrusions and cybersecurity attacks.
The AI/ ML is usually run in a batch mode and if deployed on edge nodes, most common models fail to deliver quality insights with limited data and compute capabilities. Our innovation focuses on peer-to-peer collaboration across the edge nodes to overcome the limitations of limited resources and embedding structured intelligence. The self-learning capabilities of the preoperatory cognitive models are designed to support interoperability, automated control, extreme scalability, and extensibility with minimum customization at the time of deployment. Thus, the analytical and execution models introduce a responsive decision support system on the edge that could adapt to ever-changing physical conditions and prevent cybersecurity attacks by detecting anomalies of any intrusive actions/ requests.
Serving the Global Market with Sufficient Engagements
The core competencies and platform offerings are going to be a strong enabler of next-generation intelligent systems. The mission is to focus on innovation that addresses the growing concerns of sustainability, managing disasters, and make the emerging trends of AI and IoT accessible to all types of business and industry segments across the globe. The team has been working closely with cleantech and EV solutions providers to design automated monitoring and control systems that can minimize the cost of operation, real-time asset management, and microgrid automation.
The company is engaged with industrial control manufactures, OEMs, and service amantadine firms to complement their core offerings with intuitive digital platforms to introduce intelligent process motoring and value-added services.
The hardware and software can be configured and deployed within a short window of the implementation cycle. The managed cloud-based implementation allows clients to start at a small scale to run a proof-of-concept and uncover the potential of cognitive IoT. Being an edge native solution, this platform has a very limited dependency on large IT infrastructure or mobile/ wireless network bandwidth. Moreover, the technology can be ported over the existing automation to maximize the ROI through complementary service provisioning. Therefore, organization of any geographic location, size, and scale can avail the power of innovation Ranial Systems is extending to the global market.
Offering Co-Innovation Services: Set Priorities
The 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. Prasenjit Bhadra, CEO, and Founder is an eminent scholar profile researcher and among few global technology leaders who had promoted edge-centric M2M/IoT platform design best practices and led the innovative implementation of edge computing in industrial, utilities, and public sectors in the last two decades. His experience, vision, and thought leadership has helped Ranial to gain significant mindshare and set priorities on the R&D and go-to-market initiatives.
In the current state of engagement, Ranial offers co-innovation services to the mainstream engineering firms, OEMs, and cleantech corporations where the innovations are accelerated through the digital platform. The company is extending its partnership channels to the cloud solution providers and industrial automation companies that can offer unique differentiators by integrating the technologies to enable real-time operational intelligence.
Embracing Barriers Promotes Flexibility
The exponential growth in deploying sensors and smart operations has introduced diverse applications meeting custom needs. Off-the-shelf platforms are designed to capture processes —analyze the IoT data that are implemented with custom design, yet serving almost the same set of use cases. With the current level of maturity, the industry is lacking standards and open architectures to embrace the future state of automation needs.
The hypes around edge intelligence have not gained enough traction in the marketplace. Ranial’s IP is introducing a generic set of models that require minimum customization to meet the strategic imperatives. Large players will continue to introduce proprietary hardware and software solutions that are not flexible enough to introduce the platform components.
Hence, the company has been focusing on the industries at an early stage of the adoption of IoT systems and is keen to gain competitive advantages with real-time process automation. Unless a significant investment is made on contemporary IoT platforms, the technology and platform can always complement the existing automation and allow clients to plan phase-wise transformation.
Future Strategy Through Power of Intelligence
“We believe that the profound innovation should address global imperatives and opportunities irrespective of the maturity of underlying ecosystem. Our platforms are designed to minimize the dependency on reliable networks with significant bandwidth and massive IT infrastructure. Such capabilities of our solutions are advancing through our active engagements and are supporting organizations of any scale across the world”, added Prasenjit. The emerging trends of scaling industrial IoT maximize interoperability, autonomy, and operational intelligence. The platform offerings are tagged to industry-specific solutions that have immediate and critical demand for cognitive operations. The team has demonstrated the power of intelligence that can significantly lower the cost of operations, minimize downtime and catastrophic failures. The 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.