Autonomous Energy-Efficient Wireless Sensor Network Platform for Home/Office Automation

Abella, Crispino S.; Bonina, Salvo; Cucuccio, Antonino; D’Angelo, Salvatore; Giustolisi, G.; Grasso, Alfio Dario; Imbruglia, Antonio; Mauro, G. S.; Nastasi, Giuseppe Antonio Maria; Palumbo, G.; Pennisi, S.; Sorbello, G.; Scuderi, A.

doi:10.1109/jsen.2019.2892604

Cited by 92 publications

(46 citation statements)

References 22 publications

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“…8 to maintain the efficiency above 45%. This extends the harvesting floor towards lower P IN levels yielding a 1.5x harvesting range compared to [19], [34]. Fig.…”

Section: A System Specifications and Transient Simulationsmentioning

confidence: 79%

An Input Power-Aware Efficiency Tracking Technique With Discontinuous Charging for Energy Harvesting Applications

2020

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This paper proposes a discontinuous charging technique for switched-capacitor converters that improves the power conversion efficiency (PCE) at low 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 Wireless Sensor Network (WSN) nodes is presented. In addition to conventional switching frequency control, clock non-overlap time control is introduced to adaptively optimize PCE 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. Therefore, the input power harvesting range is extended by 1.5x. The technique is applied to a wearable WSN implementation utilizing the IEEE 802.15.4-compatible GreenNet communications protocol. This allows the node to meet specifications and achieve energy autonomy when deployed in environments where the input power is 49% lower than what is required for conventional operation.

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“…8 to maintain the efficiency above 45%. This extends the harvesting floor towards lower P IN levels yielding a 1.5x harvesting range compared to [19], [34]. Fig.…”

Section: A System Specifications and Transient Simulationsmentioning

confidence: 79%

An Input Power-Aware Efficiency Tracking Technique With Discontinuous Charging for Energy Harvesting Applications

2020

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“…Smart wireless sensor nodes are expected to pervade all the emerging applications in the Internet of Things (IoT) arena [2]. Indeed, many WSN platforms aimed at enhancing services, comfort, security, and energy saving have already been proposed for smart city and home and office automation scenarios [3][4][5][6][7][8][9]. WSNs also lend themselves very well to asset-monitoring applications though their ability to monitor and record the exact positions and transportation conditions of assets, personal objects, and the like [10].…”

Section: Introductionmentioning

confidence: 99%

Advanced Monitoring Systems Based on Battery-Less Asset Tracking Modules Energized through RF Wireless Power Transfer

Rosa

Dehollain

Livreri

2020

Sensors

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Asset tracking involving accurate location and transportation data is highly suited to wireless sensor networks (WSNs) featuring battery-less nodes that can be deployed in virtually any environment and require little or no maintenance. In response to the growing demand for advanced battery-less sensor tag solutions, this article presents a system for identifying and monitoring the speeds of assets in a WSN with battery-less tags that receive all their operating energy through radio frequency (RF) wireless power transfer (WPT) architecture, and a unique measurement approach to generate time-domain speed readouts. The assessment includes performance characteristics and key features of a system on chip (SoC) purposely designed to power a node through RF WPT. The result is an innovative solution for RF to DC conversion able to address the principal difficulties associated with maximum power conversion efficiency (PCE) with sensitivity and vice versa, a strategy, and a design optimization model to indicate the number of readers required for reliable asset identification and speed measurement. Model validation is performed through specific tests. Experimental results demonstrating the viability of the proposed advanced monitoring system are provided.

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“…In order to reach the demands of the next IoT applications that require a huge number of interconnected wireless network nodes, an autonomous energy-efficient WSN platform for home/office automation applications is investigated in (8) using an optimized power management strategy and an embedded photovoltaic panel linked to a rechargeable battery. To flexibly design the applications of high-level-based techniques, a detailed study of model-based approaches and existing programming methodologies for the development of sensor networks is given in (9) .…”

Section: Introductionmentioning

confidence: 99%

Implementation of scalable and energy efficient WSN platform for IoT applications

Uqaili¹

2020

IJST

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Background/Objectives: The major problems in WSN are the short-range of RF signals and the short life of batteries of each node. We develop a platform that uses the MAC protocols to avoid collisions between packets and decrease the data collection time. To overcome the energy challenges, the sleep modes, idle consumption, and others solutions provided to extend the node’s life period Methods/Statistical analysis: Based on the IoT applications, we configured different hardware (HW) to collect data from temperature,relative humidity (RH), and carbon dioxide (CO2), and access to this data, and these devices remotely through the internet. For this, the nodes, transceivers, batteries, and the gateway (GW) are analyzed. Additionally, it is configured with the frequency band or the radio frequency (RF) sensitivity to improve the performance of the system developed. Findings: Sensors, repeaters, and the GW were configured to work with each other and be accessed through the internet. The energy consumed on the experiment carried out has been reduced by more than 80% choosing LP modes and enable sleep algorithms over the Node’s OS where the time was also reduced around 80% in comparison with the available options. By set MQTT and SSH services, this application is scalable to be integrated with cloud services and be accessed by remote computers. Novelty/Applications: Finally, the lifelong period of nodes augmented drastically, more range between nodes is achieved and highly reliable data collected with low power consumption. Keywords: WSN; sensors; IoT; CO 2; temperature; relative humidity (RH)

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Autonomous Energy-Efficient Wireless Sensor Network Platform for Home/Office Automation

Cited by 92 publications

References 22 publications

An Input Power-Aware Efficiency Tracking Technique With Discontinuous Charging for Energy Harvesting Applications

An Input Power-Aware Efficiency Tracking Technique With Discontinuous Charging for Energy Harvesting Applications

Advanced Monitoring Systems Based on Battery-Less Asset Tracking Modules Energized through RF Wireless Power Transfer

Implementation of scalable and energy efficient WSN platform for IoT applications

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