Advances in micro-electronics and miniaturized mechanical systems are redefining the scope and extent of the energy constraints found in battery-operated wireless sensor networks (WSNs). On one hand, ambient energy harvesting may prolong the systems’ lifetime or possibly enable perpetual operation. On the other hand, wireless energy transfer allows systems to decouple the energy sources from the sensing locations, enabling deployments previously unfeasible. As a result of applying these technologies to WSNs, the assumption of a finite energy budget is replaced with that of potentially infinite, yet intermittent, energy supply, profoundly impacting the design, implementation, and operation of WSNs. This article discusses these aspects by surveying paradigmatic examples of existing solutions in both fields and by reporting on real-world experiences found in the literature. The discussion is instrumental in providing a foundation for selecting the most appropriate energy harvesting or wireless transfer technology based on the application at hand. We conclude by outlining research directions originating from the fundamental change of perspective that energy harvesting and wireless transfer bring about.

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Energy Harvesting and Wireless Transfer in Sensor Network Applications: Concepts and Experiences

Corrosion has been a great concern in the oil and natural gas industry costing billions of dollars annually in the U.S. The ability to monitor corrosion online before structural integrity is compromised can have a significant impact on preventing catastrophic events resulting from corrosion. This article critically reviews conventional corrosion sensors and emerging sensor technologies in terms of sensing principles, sensor designs, advantages, and limitations. Conventional corrosion sensors encompass corrosion coupons, electrical resistance probes, electrochemical sensors, ultrasonic testing sensors, magnetic flux leakage sensors, electromagnetic sensors, and in-line inspection tools. Emerging sensor technologies highlight optical fiber sensors (point, quasi-distributed, distributed) and passive wireless sensors such as passive radio-frequency identification sensors and surface acoustic wave sensors. Emerging sensors show great potential in continuous real-time in-situ monitoring of oil and natural gas infrastructure. Distributed chemical sensing is emphasized based on recent studies as a promising method to detect early corrosion onset and monitor corrosive environments for corrosion mitigation management. Additionally, challenges are discussed including durability and stability in extreme and harsh conditions such as high temperature high pressure in subsurface wellbores.

https://www.mdpi.com/1424-8220/19/18/3964/pdf

Corrosion Sensors for Structural Health Monitoring of Oil and Natural Gas Infrastructure: A Review

In this study, a multi-clustering algorithm based on fuzzy logic (MCFL) with an entirely different approach is presented to carry out node clustering in wsn. This approach minimizes energy dissipation and, consequently, prolongs network lifetime. In the past, numerous algorithms were tasked with clustering nodes in wireless sensors networks. The common denominator of all these approaches is the constancy of the algorithm in all the rounds of network lifetime that causes the selection of cluster heads in each round. Selecting cluster heads in each round indicates that throughout the process the most eligible nodes are not selected. By comparing the chance of each node to be selected as a cluster head using a random number, the majority of these clustering approaches, both fuzzy and non-fuzzy, destroy the chance of selecting the most eligible node as cluster head. As a result, all these approaches require the selection of cluster heads in each round. Performing selections in each round increases the rate of sent and received messages. By increasing the number of messages, the total number of sent messages in the network increases too. Therefore, in a network with a high number of nodes, any increase in the number of packets will augment network traffic and increase the collision probability. On the other hand, since nodes lose a certain amount of energy for each sent message, by increasing the number of messages, nodes’ energy will correspondingly decrease which results in their premature death. However, by selecting the most eligible nodes as cluster heads and trusting them for at least a few rounds, the amount of sent and received messages is reduced. In this article, In addition to clustering nodes in different rounds using different clustering algorithms, MCFL avoids selecting new cluster heads by trusting previous cluster heads leading to a reduction in the number of messages and saving energy. MCFL is compared with other approaches in three different scenarios using indices such as total remaining energy, the number of dead nodes, first node dies, half of nodes die, and last node dies. Results reveal that MCFL has as advantage over other approaches.

MCFL: an energy efficient multi-clustering algorithm using fuzzy logic in wireless sensor network

Three ultra-high frequency (UHF) radio-frequency identification (RFID) tag antenna-based sensor designs for steel corrosion sensing with miniaturization are proposed in this paper. To characterize corrosion, a new antenna adopts the structure of patch antenna with a meanderline feed based on microstrip line theory. The impedance change of the meanderline feed results in detuning in the tag antenna so that this change can be captured with threshold power of the tag. Folded antenna with 3-D structure has been redesigned for miniaturization from the non-folded antenna to reduce the antenna size for spatial resolution enhancement, but the gain is reduced as well as sensitivity. A T-shape antenna is proposed to increase the gain of the miniaturized antenna and the sensitivity. Experimental studies with ThingMagic development kit on dedicated corrosion samples have been undertaken to validate the antenna designs. Resonant frequency features of the developed antenna are studied for corrosion characterization, but the bandwidth of UHF RFID limits the measurement range. Principal component analysis method is applied to evaluate different corrosion stages and reduce environmental interference.

Miniaturization of UHF RFID Tag Antenna Sensors for Corrosion Characterization

The Internet of Things (IoT) is a constantly-evolving area of research and touches almost every aspect of life in the modern world. As technology moves forward, it is becoming increasingly important for these IoT devices for environmental sensing to become self-powered to enable long-term operation. This paper provides an outlook on the current state-of-the-art in terms of energy harvesting for these low-power devices. An analytical approach is taken, first defining types of environments in which energy-harvesters operate, before exploring both well-known and novel energy harvesting techniques and their uses in modern-day sensing.

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Powering the Environmental Internet of Things.

Effective link interference model in topology control of wireless Ad hoc and sensor networks

This paper proposes a new clustering scheme for wireless sensor networks, which efficiently balances the energy usage inter- and intra-clusters, by using the k - medoids method and the intra-cluster head update policy. Particularly, we propose a simple-but-effective routing tree algorithm to maintain a dynamic energy-efficient tree structure over all cluster heads, in order to further reduce the energy consumption for those heads to relay data to the sink. We also conduct simulations with realistic configurations to evaluate our design in terms of system lifetime, by comparing with LEACH. The experimental results show the efficiency and effectiveness of our work.

Dynamic Cluster-based Routing for Wireless Sensor Networks

To guarantee the continuous coverage of the rechargeable sensors, Wireless Rechargeable Sensor Networks (WRSNs) has emerged with the advantages of high charging efficiency and reliable charging timeliness. Charging planning is an important problem in theoretical research and practical applications, and it faces more difficulties and challenges for multiple mobile chargers. In this paper, we introduce a charging planning problem for multiple chargers, namely Charging Energy Efficiency Maximization problem for Multi-Chargers in WRSNs (CEEM-MC Problem), and prove its NP-hardness. The problem aims to maximize the charging energy efficiency of the charging process by assigning the charging amount and planning the charging path. To balance the charging consumption among multiple chargers, we propose two algorithms which are different on the charging path planning, Ring-Wandering Algorithm and Eight-Wandering Algorithm. To evaluate the performance on energy efficiency, we perform a series of simulations and the results verify the effectiveness of the proposed algorithms. 

Energy efficiency optimization for multiple chargers in Wireless Rechargeable Sensor Networks

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.

https://www.mdpi.com/1424-8220/13/12/17414/pdf

Events as Power Source: Wireless Sustainable Corrosion Monitoring

AbstractThis paper investigates a new UAV-assisted Wireless Rechargeable Sensor Network (WRSNs) based on wireless powered technologies, where the Unmanned Aerial Vehicle (UAV) can not only be used as wireless aerial mobile base station for gathering data from sensors but also be used as mobile charger to replenish energy for sensors, and it also can be charged energy by Laser Beam Directors (LBDs) to overcome the limitation of on-board energy shortage. In such a network, we study the average Age of Information Optimization (AoIO) problem whose objective is to minimize the average AoI of data collected from sensors by UAV. We first prove that the AoIO problem is NP-hard. Since the average AoI depends on UAV’s flight trajectory, the hovering time required for data collection, energy power transfer and laser charging, we propose an approximation algorithm to solve the AoIO problem by jointly optimizing these factors. Afterwards, we conduct extensive simulation experiments to validate effectiveness of the proposed algorithm.KeywordsWRSNLaser-charged UAVAge of Information 

Zhibo Chen

Papers

Effective link interference model in topology control of wireless Ad hoc and sensor networks

Dynamic Cluster-based Routing for Wireless Sensor Networks

Energy efficiency optimization for multiple chargers in Wireless Rechargeable Sensor Networks

Events as Power Source: Wireless Sustainable Corrosion Monitoring

AoI Minimizing of Wireless Rechargeable Sensor Network Based on Trajectory Optimization of Laser-Charged UAV