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1. Heuristic Adaptation for Intermittently Powered Batteryless Sensors

   https://doi.org/10.1145/3551670.3551678  

   Bakar, Abu; Ross, Alexander G.; Sinan Yildirim, Kasim; Hester, Josiah (July 2022, GetMobile: Mobile Computing and Communications)

   Battery-free sensing devices harvest energy from their surrounding environment to perform sensing, computation, and communication. A core challenge for these devices is maintaining usefulness despite erratic, random, or irregular energy availability, which causes inconsistent execution, loss of service, and power failures. Adapting execution (degrading or upgrading) based on available or predicted power/energy seems promising to stave off power failures, meet deadlines, or increase throughput. However, due to constrained resources and limited local information, deciding what and when exactly to adapt is challenging. This article explores the fundamentals of energy-aware adaptation for intermittently powered computers and proposes heuristic adaptation mechanisms to dynamically modulate the program complexity at run-time to enable higher sensor coverage and throughput. While we target battery-free, intermittently powered, resource-constrained sensors, we see a general application to all energy harvesting devices. 

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2. On-Body Piezoelectric Energy Harvesters through Innovative Designs and Conformable Structures

   https://doi.org/10.1021/acsbiomaterials.1c00800  

   Fernandez, Sara V.; Cai, Fiona; Chen, Sophia; Suh, Emma; Tiepelt, Jan; McIntosh, Rachel; Marcus, Colin; Acosta, Daniel; Mejorado, David; Dagdeviren, Canan (October 2021, ACS Biomaterials Science & Engineering)

   Recent advancements in wearable technology have improved lifestyle and medical practices, enabling personalized care ranging from fitness tracking, to real-time health monitoring, to predictive sensing. Wearable devices serve as an interface between humans and technology; however, this integration is far from seamless. These devices face various limitations such as size, biocompatibility, and battery constraints wherein batteries are bulky, are expensive, and require regular replacement. On-body energy harvesting presents a promising alternative to battery power by utilizing the human body’s continuous generation of energy. This review paper begins with an investigation of contemporary energy harvesting methods, with a deep focus on piezoelectricity. We then highlight the materials, configurations, and structures of such methods for self-powered devices. Here, we propose a novel combination of thin-film composites, kirigami patterns, and auxetic structures to lay the groundwork for an integrated piezoelectric system to monitor and sense. This approach has the potential to maximize energy output by amplifying the piezoelectric effect and manipulating the strain distribution. As a departure from bulky, rigid device design, we explore compositions and microfabrication processes for conformable energy harvesters. We conclude by discussing the limitations of these harvesters and future directions that expand upon current applications for wearable technology. Further exploration of materials, configurations, and structures introduce interdisciplinary applications for such integrated systems. Considering these factors can revolutionize the production and consumption of energy as wearable technology becomes increasingly prevalent in everyday life. 

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3. Lab-on-a-Chip Systems for Aptamer-Based Biosensing

   https://doi.org/10.3390/mi11020220  

   Khan, Niazul I.; Song, Edward (February 2020, Micromachines)

   null (Ed.)

   Aptamers are oligonucleotides or peptides that are selected from a pool of random sequences that exhibit high affinity toward a specific biomolecular species of interest. Therefore, they are ideal for use as recognition elements and ligands for binding to the target. In recent years, aptamers have gained a great deal of attention in the field of biosensing as the next-generation target receptors that could potentially replace the functions of antibodies. Consequently, it is increasingly becoming popular to integrate aptamers into a variety of sensing platforms to enhance specificity and selectivity in analyte detection. Simultaneously, as the fields of lab-on-a-chip (LOC) technology, point-of-care (POC) diagnostics, and personal medicine become topics of great interest, integration of such aptamer-based sensors with LOC devices are showing promising results as evidenced by the recent growth of literature in this area. The focus of this review article is to highlight the recent progress in aptamer-based biosensor development with emphasis on the integration between aptamers and the various forms of LOC devices including microfluidic chips and paper-based microfluidics. As aptamers are extremely versatile in terms of their utilization in different detection principles, a broad range of techniques are covered including electrochemical, optical, colorimetric, and gravimetric sensing as well as surface acoustics waves and transistor-based detection. 

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4. Bioelectronic Sensor Nodes for the Internet of Bodies

   https://doi.org/10.1146/annurev-bioeng-110220-112448  

   Chatterjee, Baibhab; Mohseni, Pedram; Sen, Shreyas (June 2023, Annual Review of Biomedical Engineering)

   Energy-efficient sensing with physically secure communication for biosensors on, around, and within the human body is a major area of research for the development of low-cost health care devices, enabling continuous monitoring and/or secure perpetual operation. When used as a network of nodes, these devices form the Internet of Bodies, which poses challenges including stringent resource constraints, simultaneous sensing and communication, and security vulnerabilities. Another major challenge is to find an efficient on-body energy-harvesting method to support the sensing, communication, and security submodules. Due to limitations in the amount of energy harvested, we require a reduction in energy consumed per unit information, making the use of in-sensor analytics and processing imperative. In this article, we review the challenges and opportunities of low-power sensing, processing, and communication with possible powering modalities for future biosensor nodes. Specifically, we analyze, compare, and contrast ( a) different sensing mechanisms such as voltage/current domain versus time domain, ( b) low-power, secure communication modalities including wireless techniques and human body communication, and ( c) different powering techniques for wearable devices and implants. 

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5. Intelligent Networking for Energy Harvesting Powered IoT Systems

   https://doi.org/10.1145/3638765  

   Zhang, Wen; Pan, Chen; Liu, Tao; Zhang, Jeff Jun; Sookhak, Mehdi; Xie, Mimi (March 2024, ACM Transactions on Sensor Networks)

   As the next-generation battery substitute for IoT system, energy harvesting (EH) technology revolutionizes the IoT industry with environmental friendliness, ubiquitous accessibility, and sustainability, which enables various self-sustaining IoT applications. However, due to the weak and intermittent nature of EH power, the performance of EH-powered IoT systems as well as its collaborative routing mechanism can severely deteriorate, rendering unpleasant data package loss during each power failure. Such a phenomenon makes conventional routing policies and energy allocation strategies impractical. Given the complexity of the problem, reinforcement learning (RL) appears to be one of the most promising and applicable methods to address this challenge. Nevertheless, although the energy allocation and routing policy are jointly optimized by the RL method, due to the energy restriction of EH devices, the inappropriate configuration of multi-hop network topology severely degrades the data collection performance. Therefore, this article first conducts a thorough mathematical discussion and develops the topology design and validation algorithm under energy harvesting scenarios. Then, this article developsDeepIoTRouting, a distributed and scalable deep reinforcement learning (DRL)-based approach, to address the routing and energy allocation jointly for the energy harvesting powered distributed IoT system. The experimental results show that with topology optimization,DeepIoTRoutingachieves at least 38.71% improvement on the amount of data delivery to sink in a 20-device IoT network, which significantly outperforms state-of-the-art methods. 

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