Energy Harvesting Chip and the Chip Based Power Supply Development for a Wireless Sensor Network

A Self-Powered and Battery-Free Vibrational Energy to Time Converter for Wireless Vibration Monitoring

Wireless sensor nodes (WSNs) are the fundamental part of an Internet of Things (IoT) system for detecting and transmitting data to a master node for processing. Several research studies reveal that one of the disadvantages of conventional, battery-powered WSNs, however, is that they typically require periodic maintenance. This paper aims to contribute to existing research studies on this issue by exploring a new energy-autonomous and battery-free WSN concept for monitor vibrations. The node is self-powered from the conversion of ambient mechanical vibration energy into electrical energy through a piezoelectric transducer implemented with lead-free lithium niobate piezoelectric material to also explore solutions that go towards a greener and more sustainable IoT. Instead of implementing any particular sensors, the vibration measurement system exploits the proportionality between the mechanical power generated by a piezoelectric transducer and the time taken to store it as electrical energy in a capacitor. This helps reduce the component count with respect to conventional WSNs, as well as energy consumption and production costs, while optimizing the overall node size and weight. The readout is therefore a function of the time it takes for the energy storage capacitor to charge between two constant voltage levels. The result of this work is a system that includes a specially designed lead-free piezoelectric vibrational transducer and a battery-less sensor platform with Bluetooth low energy (BLE) connectivity. The system can harvest energy in the acceleration range [0.5 g–1.2 g] and measure vibrations with a limit of detection (LoD) of 0.6 g.

Energy Management for Energy Harvesting-Based Embedded Systems: A Systematic Mapping Study

Energy management for energy harvesting-based embedded systems (EHES) is an emerging field, which aims to collect renewable energy from the environment to power an embedded system. In this work, we use the systematic mapping method to study the relevant literature, with the objective of exploring and analysing the state of the art in energy management for EHES, as well as to provide assistance for subsequent literature reviews. To this end, we conducted extensive searches to find articles related to energy harvesting, embedded systems, energy consumption, and energy management. We searched for papers from January 2005 to July 2019 from three mainstream databases, ACM, IEEE Xplore, and Web of Science, and found more than 3000 papers about EHES. Finally, we selected 142 eligible papers. We have completed the system mapping research from five aspects, namely, (1) research type (validation research, evaluation research, solution proposal, philosophical paper, opinion, and experience), (2) research goals (application or theory), (3) application scenarios, (4) tools or methods, and (5) paper distribution, such as publication year and authors’ nationality. The results showed that the major research type of the EHES papers is validation research, accounting for 65%, which indicated research is still in the theoretical stage and many researchers focus on how to improve the efficiency of harvesting energy, develop a reasonable energy supply plan, and adapt EHES for real-world requirements. Furthermore, this work reviews the tools used for EHES. As the future development direction, it is indispensable to provide tools to EHES for research, testing, development, and so on. The results of our analysis provide significant contributions to understanding the existing knowledge and highlighting potential future research opportunities in the EHES field.

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

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.

Strategies and Techniques for Powering Wireless Sensor Nodes through Energy Harvesting and Wireless Power Transfer

The continuous development of internet of things (IoT) infrastructure and applications is paving the way for advanced and innovative ideas and solutions, some of which are pushing the limits of state-of-the-art technology. The increasing demand for Wireless Sensor Nodes (WSNs) able to collect and transmit data through wireless communication channels, while often positioned in locations that are difficult to access, is driving research into innovative solutions involving energy harvesting (EH) and wireless power transfer (WPT) to eventually allow battery-free sensor nodes. Due to the pervasiveness of radio frequency (RF) energy, RF EH and WPT are key technologies with the potential to power IoT devices and smart sensing architectures involving nodes that need to be wireless, maintenance free, and sufficiently low in cost to promote their use almost anywhere. This paper presents a state-of-the-art, ultra-low power 2.5 μ W highly integrated mixed signal system on chip (SoC), for multi-source energy harvesting and wireless power transfer. It introduces a novel architecture that integrates an ultra-low power intelligent power management, an RF to DC converter with very low power sensitivity and high power conversion efficiency (PCE), an Amplitude-Shift-Keying/Frequency-Shift-Keying (ASK/FSK) receiver and digital circuitry to achieve the advantage to cope, in a versatile way and with minimal use of external components, with the wide variety of energy sources and use cases. Diverse methods for powering Wireless Sensor Nodes through energy harvesting and wireless power transfer are implemented providing related system architectures and experimental results.

Enabling Smart Air Conditioning by Sensor Development: A Review

The study investigates the development of sensors, in particular the use of thermo-fluidic sensors and occupancy detectors, to achieve smart operation of air conditioning systems. Smart operation refers to the operation of air conditioners by the reinforcement of interaction to achieve both thermal comfort and energy efficiency. Sensors related to thermal comfort include those of temperature, humidity, and pressure and wind velocity anemometers. Improvements in their performance in the past years have been studied by a literature survey. Traditional occupancy detection using passive infra-red (PIR) sensors and novel methodologies using smartphones and wearable sensors are both discussed. Referring to the case studies summarized in this study, air conditioning energy savings are evaluated quantitatively. Results show that energy savings of air conditioners before 2000 was 11%, and 30% after 2000 by the integration of thermo-fluidic sensors and occupancy detectors. By utilizing wearable sensing to detect the human motions, metabolic rates and related information, the energy savings can reach up to 46.3% and keep the minimum change of predicted mean vote (∆PMV→0), which means there is no compromise in thermal comfort. This enables smart air conditioning to compensate for the large variations from person to person in terms of physiological and psychological satisfaction, and find an optimal temperature for everyone in a given space. However, this tendency should be evidenced by more experimental results in the future.

The benefits of soft sensor and multi-rate control for the implementation of Wireless Networked Control Systems

Recent advances in wireless networking technology and the proliferation of industrial wireless sensors have led to an increasing interest in using wireless networks for closed loop control. The main advantages of Wireless Networked Control Systems (WNCSs) are the reconfigurability, easy commissioning and the possibility of installation in places where cabling is impossible. Despite these advantages, there are two main problems which must be considered for practical implementations of WNCSs. One problem is the sampling period constraint of industrial wireless sensors. This problem is related to the energy cost of the wireless transmission, since the power supply is limited, which precludes the use of these sensors in several closed-loop controls. The other technological concern in WNCS is the energy efficiency of the devices. As the sensors are powered by batteries, the lowest possible consumption is required to extend battery lifetime. As a result, there is a compromise between the sensor sampling period, the sensor battery lifetime and the required control performance for the WNCS. This paper develops a model-based soft sensor to overcome these problems and enable practical implementations of WNCSs. The goal of the soft sensor is generating virtual data allowing an actuation on the process faster than the maximum sampling period available for the wireless sensor. Experimental results have shown the soft sensor is a solution to the sampling period constraint problem of wireless sensors in control applications, enabling the application of industrial wireless sensors in WNCSs. Additionally, our results demonstrated the soft sensor potential for implementing energy efficient WNCS through the battery saving of industrial wireless sensors.

Events as power source: wireless sustainable corrosion monitoring

This study presents and implements a corrosion-monitoring wireless sensor platform, EPS (Events as Power Source), which monitors the corrosion events in reinforced concrete (RC) structures, while being powered by the micro-energy released from the corrosion process. In EPS, the proposed corrosion-sensing device serves both as the signal source for identifying corrosion and as the power source for driving the sensor mote, because the corrosion process (event) releases electric energy; this is a novel idea proposed by this study. For accumulating the micro-corrosion energy, we integrate EPS with a COTS (Commercial Off-The-Shelf) energy-harvesting chip that recharges a supercapacitor. In particular, this study designs automatic energy management and adaptive transmitted power control polices to efficiently use the constrained accumulated energy. Finally, a set of preliminary experiments based on concrete pore solution are conducted to evaluate the feasibility and the efficacy of EPS.

Integrated Thin-Film Rechargeable Battery on α-Si Thin-Film Solar Cell

In this paper we reported on fabrication and characterization of a composite harvesting device integrated thin-film rechargeable battery on α-Si thin-film solar cell. The α-Si thin-film solar cell typically presented open-circuit voltage of 4.3 V, short-circuit current of 15.4 mA/cm2 and efficiency of 7.4%. The thin-film rechargeable battery composed of Nb2O5/LiPON/LiMn2O4 systems fabricated using dry process, which showed the initial discharge capacity of about 215 μAh (or 12.4 μAh/cm2), the cycleabilty for discharge was good at keeping about 12.3 μAh/cm2 with a small decreasing ratio of 0.1% per cycle and the coulombic efficiency was all over 95% for the 100 cycles. On the other hand, the discharge capacity of approximately 80% was provided by the self-charging of the solar cell for 10 min, and the coulombic efficiency was also over 95%.

Open-WiSe: a solar powered wireless sensor network platform

Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators.

Investigation of electrical and magnetic properties of ferro-nanofluid on transformers

This study investigated a simple model of transformers that have liquid magnetic cores with different concentrations of ferro-nanofluids. The simple model was built on a capillary by enamel-insulated wires and with ferro-nanofluid loaded in the capillary. The ferro-nanofluid was fabricated by a chemical co-precipitation method. The performances of the transformers with either air core or ferro-nanofluid at different concentrations of nanoparticles of 0.25, 0.5, 0.75, and 1 M were measured and simulated at frequencies ranging from 100 kHz to 100 MHz. The experimental results indicated that the inductance and coupling coefficient of coils grew with the increment of the ferro-nanofluid concentration. The presence of ferro-nanofluid increased resistance, yielding to the decrement of the quality factor, owing to the phase lag between the external magnetic field and the magnetization of the material.

Energy saving effects of wireless sensor networks: a case study of convenience stores in Taiwan

Wireless sensor network (WSN) technology has been successfully applied to energy saving applications in many places, and plays a significant role in achieving power conservation. However, previous studies do not discuss WSN costs and cost-recovery. The application of WSNs is currently limited to research and laboratory experiments, and not mass industrial production, largely because business owners are unfamiliar with the possible favorable return and cost-recovery on WSN investments. Therefore, this paper focuses on the cost-recovery of WSNs and how to reduce air conditioning energy consumption in convenience stores. The WSN used in this study provides feedback to the gateway and adopts the predicted mean vote (PMV) and computational fluid dynamics (CFD) methods to allow customers to shop in a comfortable yet energy-saving environment. Four convenience stores in Taipei have used the proposed WSN since 2008. In 2008, the experiment was initially designed to optimize air-conditioning for energy saving, but additions to the set-up continued beyond 2008, adding the thermal comfort and crowds peak, off-peak features in 2009 to achieve human-friendly energy savings. Comparison with 2007 data, under the same comfort conditions, shows that the power savings increased by 40% (2008) and 53% (2009), respectively. The cost of the WSN equipment was 500 US dollars. Experimental results, including three years of analysis and calculations, show that the marginal energy conservation benefit of the four convenience stores achieved energy savings of up to 53%, recovering all costs in approximately 5 months. The convenience store group participating in this study was satisfied with the efficiency of energy conservation because of the short cost-recovery period.

Applications of ferro-nanofluid on a micro-transformer

An on-chip transformer with a ferrofluid magnetic core has been developed and tested. The transformer consists of solenoid-type coil and a magnetic core of ferrofluid, with the former fabricated by MEMS technology and the latter by a chemical co-precipitation method. The performance of the MEMS transformer with a ferrofluid magnetic core was measured and simulated with frequencies ranging from 100 kHz to 100 MHz. Experimental results reveal that the presence of the ferrofluid increases the inductance of coils and the coupling coefficient of transformer; however, it also increases the resistance owing to the lag between the external magnetic field and the magnetization of the material.

Signal quality classification for an ambulatory monitoring system

A signal quality classification algorithm is presented to evaluate signal quality in ambulatory monitoring system. Acoustic based signal is classified as good signal, weak signal or noisy signal. Certain features in the acquired signal are extracted and analyzed to differentiate the class of signal quality. With this classification, wrong physiological estimation due to poor signal quality can be eliminated to avoid wrong conclusions and instructions in the ambulatory system.