3 research outputs found

    Software controlled low cost thermoelectric energy harvester for ultra-low power wireless sensor nodes

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    General hardware architecture of an energy-harvested wireless sensor network node (EH-WSN) can be divided into power, sensing, computing and communication subsystems. Interrelation between these subsystems in combination with constrained energy supply makes design and implementation of EH-WSN a complex and challenging task. Separation of these subsystems into distinct hardware modules simplifies the design process and makes the architecture and software more generic, leading to more flexible solutions. From the other hand, tightly coupling these subsystems gives more room for optimizations at the price of increased complexity of the hardware and software. Additional engineering effort could be justified by a smaller, cheaper hardware, and more energy-efficient a wireless sensor node. The aim of this paper is to push further technical and economical boundaries related to EH-WSN by proposing a novel architecture which – by tightly coupling software and hardware of power, computing, and communication subsystems – allows the wireless sensor node to be powered by a thermoelectric generator working with about 1.5°C temperature difference while keeping the cost of all electronic components used to build such a node below 9 EUR (in volume)

    A survey on short-range WBAN communication; technical overview of several standard wireless technologies

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    In a healthy environment, a WBAN system is the key component or aspect of the patient monitoring system. WBAN systems allow for easy networking with other devices and networks so that healthcare professionals can easily access critical and non-critical patient data. One of the main advantages of WBAN is the remote monitoring of patients using an Intranet or the Internet. There are two main components to the type of communication technology used in WBAN. This page shows an insight of a variety of short-range standardized wireless devices, as well as a taxonomy of short-range technologies. These are proposed as intra-BAN communication candidates for communication within and between body area network (BAN) entities. This paper also highlights the advantages and disadvantages of the WBAN perspective. Finally, a side-by-side comparison of the basic principles of using MICS frequency bands and preparatory technologies

    An Input Power-Aware Maximum Efficiency Tracking Technique for Energy Harvesting in IoT Applications

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    The Internet of Things (IoT) enables intelligent monitoring and management in many applications such as industrial and biomedical systems as well as environmental and infrastructure monitoring. As a result, IoT requires billions of wireless sensor network (WSN) nodes equipped with a microcontroller and transceiver. As many of these WSN nodes are off-grid and small-sized, their limited-capacity batteries need periodic replacement. To mitigate the high costs and challenges of these battery replacements, energy harvesting from ambient sources is vital to achieve energy-autonomous operation. Energy harvesting for WSNs is challenging because the available energy varies significantly with ambient conditions and in many applications, energy must be harvested from ultra-low power levels. To tackle these stringent power constraints, this dissertation proposes a discontinuous charging technique for switched-capacitor converters that improves the power conversion efficiency (PCE) at low input power levels and extends the input power harvesting range at which high PCE is achievable. Discontinuous charging delivers current to energy storage only during clock non-overlap time. This enables tuning of the output current to minimize converter losses based on the available input power. Based on this fundamental result, an input power-aware, two-dimensional efficiency tracking technique for WSNs is presented. In addition to conventional switching frequency control, clock nonoverlap time control is introduced to adaptively optimize the power conversion efficiency according to the sensed ambient power levels. The proposed technique is designed and simulated in 90nm CMOS with post-layout extraction. Under the same input and output conditions, the proposed system maintains at least 45% PCE at 4μW input power, as opposed to a conventional continuous system which requires at least 18.7μW to maintain the same PCE. In this technique, the input power harvesting range is extended by 1.5x. The technique is applied to a WSN implementation utilizing the IEEE 802.15.4- compatible GreenNet communications protocol for industrial and wearable applications. This allows the node to meet specifications and achieve energy autonomy when deployed in harsher environments where the input power is 49% lower than what is required for conventional operation
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