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The current landscape in the twenty-first century has become exceedingly complex and interconnected by resources, systems, and networks, both physical and virtual. Using cyber-physical systemsCyber-Physical Systems (CPS) (CPS), the Internet of Things (IoT)Internet of Things (IoT) based devices form highly connected and adaptive environmentsEnvironment through smart and intelligent systems and protocols to provide enhanced situational awareness. Artificial intelligenceArtificial Intelligence (AI) plays a pivotal role in augmenting the potential of IoTsInternet of Things (IoT), now commonly termed AIoT. One of the constraints that limits such operations is the sources of energy to power such devices. Recent advances in next-generation triboelectric nanogeneratorsTriboelectric Nanogenerators (TENG) (TENG), the integration of finite-state machines (FSM)Finite-State Machines (FSM), and built-in edge computingEdge computing in onboard IoT devices have reduced the energy requirement, thus shifting the energy storage requirements to built-in power generation and ambient sources. Furthermore, it is essential to have the synergetic integration of technologies to minimize energy storage and reduce energy consumption in commercial off-the-shelfCommercial Off-the-Shelf (COTS) (COTS) configurations. As the complexity and functionality of systems around us increase exponentiallyExponential technologies, combinatorial technologies in conjunction with artificial intelligenceArtificial Intelligence (AI) (AI), machine learningMachine learning (ML), and data analytics (DA) are used as decision support tools to provide a comprehensive analysis and strategy to optimize usage. The economic and societal potential of such systems is vastly greater than what has been realized, and significant investments are being made worldwide to develop the technology, hence CPSCyber-Physical Systems (CPS), in conjunction with AI with IoT (AIoT)AI with IoT (AIoT) and the Internet of BehaviorInternet of Behavior (IoB) (IoB) will further expand the boundaries of smart and connected systems to provide numerous societal opportunities. Applications of AIoTsAI with IoT (AIoT), IoBInternet of Behavior (IoB), and onboard energy harvestingEnergy harvesting devices also include critical infrastructure, sensors, tactile sensing, and smart agriculture.

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Dielectric Material Parameter Optimization for Energy Harvesting in IoTs for Edge Computing

  • 会议论文

  • 发表日期：

    2026年

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  • Ashok Vaseashta,
  • Surik Khudaverdyan,
  • Gagik Ayvazyan

摘要

The current landscape in the twenty-first century has become exceedingly complex and interconnected by resources, systems, and networks, both physical and virtual. Using cyber-physical systemsCyber-Physical Systems (CPS) (CPS), the Internet of Things (IoT)Internet of Things (IoT) based devices form highly connected and adaptive environmentsEnvironment through smart and intelligent systems and protocols to provide enhanced situational awareness. Artificial intelligenceArtificial Intelligence (AI) plays a pivotal role in augmenting the potential of IoTsInternet of Things (IoT), now commonly termed AIoT. One of the constraints that limits such operations is the sources of energy to power such devices. Recent advances in next-generation triboelectric nanogeneratorsTriboelectric Nanogenerators (TENG) (TENG), the integration of finite-state machines (FSM)Finite-State Machines (FSM), and built-in edge computingEdge computing in onboard IoT devices have reduced the energy requirement, thus shifting the energy storage requirements to built-in power generation and ambient sources. Furthermore, it is essential to have the synergetic integration of technologies to minimize energy storage and reduce energy consumption in commercial off-the-shelfCommercial Off-the-Shelf (COTS) (COTS) configurations. As the complexity and functionality of systems around us increase exponentiallyExponential technologies, combinatorial technologies in conjunction with artificial intelligenceArtificial Intelligence (AI) (AI), machine learningMachine learning (ML), and data analytics (DA) are used as decision support tools to provide a comprehensive analysis and strategy to optimize usage. The economic and societal potential of such systems is vastly greater than what has been realized, and significant investments are being made worldwide to develop the technology, hence CPSCyber-Physical Systems (CPS), in conjunction with AI with IoT (AIoT)AI with IoT (AIoT) and the Internet of BehaviorInternet of Behavior (IoB) (IoB) will further expand the boundaries of smart and connected systems to provide numerous societal opportunities. Applications of AIoTsAI with IoT (AIoT), IoBInternet of Behavior (IoB), and onboard energy harvestingEnergy harvesting devices also include critical infrastructure, sensors, tactile sensing, and smart agriculture.