International Journal For Multidisciplinary Research

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Cognitive Device Computability in Next-Generation IoT Ecosystems: A Comprehensive Framework for Distributed Computation with Privacy Preservation, Quantifiable Reasoning, and Autonomous Edge Intelligence

Author(s) Dr. Umakant Pandurang Pise
Country India
Abstract The Internet of Things (IoT) has progressed from its original state as a data-collection system to become a network of connected devices which require immediate processing capabilities. The current situation has reached a fundamental problem because there is no standardized method to determine the cognitive abilities of Internet of Things devices which must show their capability to independently detect and understand and acquire knowledge and change their behavior without accessing cloud resources. The paper presents Cognitive Device Computability (CDC) as a formalized theoretical framework which includes three original elements. The first element The Cognitive Device Quotient (CDQ) measures device intelligence through its weighted system which evaluates multiple dimensions of intelligence. The Adaptive Edge Autonomy Model (AEAM) provides organizations with a four-level system which enables them to make context-based decisions while protecting their private information through distributed reasoning. The Computability Maturity Index (CMI) functions as a five-stage ecosystem classification system which organizations can use to assess their Internet of Things deployments against cognitive autonomy criteria. The system represents Internet of Things devices as self-learning computational devices because the current system unites various optimization methods into a single framework. The operational tests conducted through simulations in industrial sectors and healthcare systems and smart city environments achieved latency times which decreased to less than 4.8 milliseconds while achieving energy reductions of 34 percent and maintaining 91.4 percent of user privacy and 96.2 percent of system functionality during network outages. The proposed framework provides an essential theoretical base together with an engineering plan that will guide development of future autonomous sustainable IoT systems which follow ethical principles.
Keywords Cognitive Device Computability, Cognitive Device Quotient, Adaptive Edge Autonomy, TinyML, Federated Edge Intelligence, Privacy-Preserving IoT, Computability Maturity Index, Distributed Autonomous Systems, Edge-Native AI, Self-Adaptive Computation.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 8, Issue 2, March-April 2026
Published On 2026-03-07
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E-ISSN 2582-2160
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