Thermoelectric Powered Autonomous Wireless Sensor Module for Temperature Monitoring

2011 ◽  
Vol 63-64 ◽  
pp. 978-982 ◽  
Author(s):  
Wen Si Wang ◽  
Ning Ning Wang ◽  
Michael Hayes ◽  
Brendan O'Flynn ◽  
Cian O'Mathuna
Keyword(s):  
Sensor Networks ◽  
Sensor Node ◽  
Energy Harvester ◽  
Electrical Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life ◽  
Wireless Sensor Node ◽  
Battery Lifetime ◽  
Sensor Module

Wireless sensor networks are frequently used to monitor temperature and other manufacturing parameters in recent years. However, the limited battery life posts a constraint for large sensor networks. In this work, thermoelectric energy harvester is designed to effectively convert the heat into electrical energy to power the wireless sensor node. Bismuth telluride thermoelectric modules are optimized for low temperature conditions. Charge pump and switching regulator based power management module is designed to efficiently step up the 500mV thermoelectric voltage to 3.0V level for wireless sensor nodes. This design employs electric double-layer capacitor based energy storage with considerations on practical wireless sensor node operation. The implemented energy harvester prototype is proposed for Tyndall wireless sensor system to monitor temperature and relative humidity in manufacturing process. The prototype was tested in various conditions to discover the issues in this practical design. The proposed prototype can expect a 15 years operative lifetime instead of the 3-6 months battery lifetime.

scholarly journals An Open-Source Wireless Sensor Node Platform with Active Node-Level Reliability for Monitoring Applications

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7613
Author(s):  
Dominik Widhalm ◽  
Karl M. Goeschka ◽  
Wolfgang Kastner
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Open Source ◽  
Sensor Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life ◽  
Active Node ◽  
Data Distortion ◽  
Monitoring Applications

In wireless sensor networks, the quality of the provided data is influenced by the properties of the sensor nodes. Often deployed in large numbers, they usually consist of low-cost components where failures are the norm, even more so in harsh outdoor environments. Current fault detection techniques, however, consider the sensor data alone and neglect vital information from the nodes’ hard- and software. As a consequence, they can not distinguish between rare data anomalies caused by proper events in the sensed data on one side and fault-induced data distortion on the other side. In this paper, we contribute with a novel, open-source sensor node platform for monitoring applications such as environmental monitoring. For long battery life, it comprises mainly low-power components. In contrast to other sensor nodes, our platform provides self-diagnostic measures to enable active node-level reliability. The entire sensor node platform including the hardware and software components has been implemented and is publicly available and free to use for everyone. Based on an extensive and long-running practical experiment setup, we show that the detectability of node faults is improved and the distinction between rare but proper events and fault-induced data distortion is indeed possible. We also show that these measures have a negligible overhead on the node’s energy efficiency and hardware costs. This improves the overall reliability of wireless sensor networks with both, long battery life and high-quality data.

Structure Design of Energy Harvester for Supporting Paroxysmal Energy Collection

2012 ◽  
Author(s):  
Zhenhuan Zhu ◽  
S. Olutunde Oyadiji
Keyword(s):  
Conversion Efficiency ◽  
Sensor Node ◽  
Energy Harvester ◽  
Energy Conversion Efficiency ◽  
Structure Design ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Random Fluctuation ◽  
Wireless Sensor Node ◽  
Power Conditioner

This paper proposes a structure of energy harvester that is used to scavenge environment energy to power wireless sensor nodes. The ambient energy usually is from sunlight, wind, vibration, and so on. As the size of a sensor node is limited, the energy converted is normally small and has a prodigious random fluctuation. In order to improve the conversion efficiency of energy harvester, the paper proposes a power conversion circuit to collect rapidly paroxysmal energy generated by external environment. The circuit, as a power conditioner, bridges between energy transducers and the load of a wireless sensor node, and the power output of transducers are either AC or DC. The power conditioner implements AC-DC conversion, voltage adjusting and energy storage. A design model is developed to describe the dynamic behavior of the power conditioner under the different excitation from ambient energy sources, and energy conversion efficiency can be evaluated with the model. The proposed system architecture can be applied in the design of solar, wind or stochastic vibration energy harvesters.

Harvesting Vibration From Rotating Machinery as a Power Source for a Wireless Sensor Node

2009 ◽  
Author(s):  
H. Salleh ◽  
N. M. Rashid ◽  
K. A. Wahib
Keyword(s):  
Integrated Circuit ◽  
Power Output ◽  
Sensor Node ◽  
Energy Harvester ◽  
Electrical Energy ◽  
Rotating Machinery ◽  
Wireless Sensor ◽  
Design Parameters ◽  
Wireless Sensor Node ◽  
In Series

The wireless sensor device which uses battery can cause problems when the wireless nodes are large in number and when the nodes are placed in the difficult area to access. Therefore, it is advantageous for the sensor node to be capable of extracting energy from the environment, making it self-powered, self-sustaining and lowering overall cost of the wireless network. Improvement in integrated circuit (IC) technology has made the overall power consumption of circuit very small which leads to a very promising application of the vibration-based energy harvester micro power generator (VEHM). This paper discusses on some practical design considerations in harvesting vibration from rotating machinery to power up a wireless sensor node. It also focuses on the effect of shape of the VEHM on its power output. These parameters are actually important as part of the key design parameters in harvesting the vibration from ambient. The energy harvester is made of piezoelectric bimorph bender materials poling in series to transform ambient vibrations into electrical energy. The power output for the VEHM made of single and multiple array of PZT bimorph bender are investigated and the effect of triangular and the rectangular PZT bimorph bender are compared. Two sets of VEHM device have been tested to work in the range of 50 Hz–110 Hz to power up a wireless sensor node for condition monitoring application. The experimental results are presented and compared to the previous similar work. It is found that the triangular shape bender generates more power compared to rectangular form whether it is single or multiple connected in series. Testing results proved that triangular VEHM of the same volume and fundamental frequency when compared to rectangular VEHM can improve the overall power generated by the generator.

scholarly journals Concurrent Data Message Transmissions for Interference of Illegal Overhearing in Wireless Sensor Networks

2018 ◽  
Vol 210 ◽  
pp. 03011
Author(s):  
Masahiro Okuri ◽  
Hiroaki Higaki
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Wireless Transmission ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Transmission Range ◽  
Wireless Sensor Node ◽  
Wireless Sensor Nodes ◽  
Wireless Nodes

In wireless sensor networks, data messages containing sensor data achieved by a sensor module in a wireless sensor node is transmitted to a stationary wireless sink node along a wireless multihop transmission route in which wireless sensor nodes themselves forward the data messages. Each intermediate wireless sensor node broadcast data messages in its wireless transmission range to forward them to its next-hop intermediate wireless sensor node. Hence, eavesdropper wireless nodes within the wireless transmission range easily overhear the data messages. In order to interfere with the eavesdropper wireless nodes illegally overhearing the data messages in transmission, wireless sensor nodes whose wireless transmission ranges overlap and their next-hop intermediate wireless sensor nodes are out of the wireless transmission ranges each other forward data messages in transmission concurrently and cause collisions between these two data messages at any possible eavesdropper wireless nodes intentionally. To enhance regions where concurrently forwarded data messages intentionally collide to prevent their overhearing and to realize concurrent forwarding of data messages, this paper designes an algorithm for TDMA transmission slot assignments for more opportunities to interfere the eavesdropper wireless nodes.

scholarly journals A Machine Learning Approach for Wear Monitoring of End Mill by Self-Powering Wireless Sensor Nodes

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3137
Author(s):  
Vytautas Ostasevicius ◽  
Paulius Karpavicius ◽  
Agne Paulauskaite-Taraseviciene ◽  
Vytautas Jurenas ◽  
Arkadiusz Mystkowski ◽  
...  
Keyword(s):  
Sensor Node ◽  
Electrical Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Support Vector ◽  
Wireless Sensor Node ◽  
End Mill ◽  
Machine Learning Approach ◽  
Wear Monitoring ◽  
Electrical Impulses

There are many tool condition monitoring solutions that use a variety of sensors. This paper presents a self-powering wireless sensor node for shank-type rotating tools and a method for real-time end mill wear monitoring. The novelty of the developed and patented sensor node is that the longitudinal oscillations, which directly affect the intensity of the energy harvesting, are significantly intensified due to the helical grooves cut onto the conical surface of the tool holder horn. A wireless transmission of electrical impulses from the capacitor is proposed, where the collected electrical energy is charged and discharged when a defined potential is reached. The frequency of the discharge pulses is directly proportional to the wear level of the tool and, at the same time, to the surface roughness of the workpiece. By employing these measures, we investigate the support vector machine (SVM) approach for wear level prediction.

scholarly journals Energy Efficiency Analysis of LoRa and ZigBee Protocols in Wireless Sensor Networks

2021 ◽  
Vol 11 (4) ◽  
pp. 2836-2849
Author(s):  
K. Raghava Rao ◽  
D. Sateesh Kumar ◽  
Mohiddin Shaw ◽  
V. Sitamahalakshmi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Power Consumption ◽  
Low Power ◽  
Sensor Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Node ◽  
Wireless Sensor Nodes ◽  
Iot Applications

Now a days IoT technologies are emerging technology with wide range of applications. Wireless sensor networks (WSNs) are plays vital role in IoT technologies. Construction of wireless sensor node with low-power radio link and high-speed processors is an interesting contribution for wireless sensor networks and IoT applications. Most of WSNs are furnished with battery source that has limited lifetime. The maximum operations of these networks require more power utility. Nevertheless, improving network efficiency and lifetime is a curtail issue in WSNs. Designing a low powered wireless sensor networks is a major challenges in recent years, it is essential to model its efficiency and power consumption for different applications. This paper describes power consumption model based on LoRa and Zigbee protocols, allows wireless sensor nodes to monitor and measure power consumption in a cyclic sleeping scenario. Experiential results reveals that the designed LoRa wireless sensor nodes have the potential for real-world IoT application with due consideration of communicating distance, data packets, transmitting speed, and consumes low power as compared with Zigbee sensor nodes. The measured sleep intervals achieved lower power consumption in LoRa as compared with Zigbee. The uniqueness of this research work lies in the review of wireless sensor node optimization and power consumption of these two wireless sensor networks for IoT applications.

scholarly journals Monitoring Penggunaan Daya listrik Sebagai Implementasi Internet of Things Berbasis Wireless Sensor Network

2017 ◽  
Vol 16 (3) ◽  
pp. 50
Author(s):  
I Gusti Putu Mastawan Eka Putra ◽  
Ida Ayu Dwi Giriantari ◽  
Lie Jasa
Keyword(s):  
Wireless Sensor Network ◽  
Internet Of Things ◽  
Sensor Network ◽  
Sensor Node ◽  
Electrical Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
The Internet ◽  
Wireless Sensor Node ◽  
Electrical Parameters

One implementation of the Internet of Things (IoT) conducted in this study to realize the system of monitoring and control of electrical energy usage-based Wireless Sensor Network (WSN). This research method is the design of wireless sensor nodes that can measure the electrical parameters of alternating current (AC) as effective voltage, effective current, active power, apparent power, power factor and total electrical energy consumption by using modules ESP8266 as a liaison with a Wi-Fi. Calculation of electrical parameters obtained from ATmega328P microcontroller ADC readings of a step-down transformer that is used as a voltage sensor and sensor SCT013 used as AC current sensors will be transmitted to the server over the network from a Wi-Fi Access Point (AP). ESP8266 modules are programmed using AT-Command proven to reliably measure can transmit data simultaneously with serial data format of the wireless sensor node to a server using TCP / IP protocol. Monitoring power consumption via the internet which are designed in the research, either through the Android application and web browser proven to be reliably able to show some electrical parameters with the same data than the data logger recaps taken from SD-Card installed in the wireless sensor node.

scholarly journals Raspberry Pi Based Intelligent Wireless Sensor Node for Localized Torrential Rain Monitoring

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Zhaozhuo Xu ◽  
Fangling Pu ◽  
Xin Fang ◽  
Jing Fu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Heavy Rain ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Raspberry Pi ◽  
Support Vector ◽  
Wireless Sensor Node ◽  
Torrential Rain

Wireless sensor networks are proved to be effective in long-time localized torrential rain monitoring. However, the existing widely used architecture of wireless sensor networks for rain monitoring relies on network transportation and back-end calculation, which causes delay in response to heavy rain in localized areas. Our work improves the architecture by applying logistic regression and support vector machine classification to an intelligent wireless sensor node which is created by Raspberry Pi. The sensor nodes in front-end not only obtain data from sensors, but also can analyze the probabilities of upcoming heavy rain independently and give early warnings to local clients in time. When the sensor nodes send the probability to back-end server, the burdens of network transport are released. We demonstrate by simulation results that our sensor system architecture has potentiality to increase the local response to heavy rain. The monitoring capacity is also raised.

scholarly journals A REVIEW ON WIRELESS SENSOR NETWORK FOR ENERGY CONSUMPTION

2016 ◽  
Vol 2 (5) ◽  
Author(s):  
Shobha Kushwaha ◽  
Deepak Tomar ◽  
Kamlesh Chandravanshi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Storage ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life ◽  
Battery Lifetime ◽  
Important Concern ◽  
Spatially Distributed

A wireless sensors network (WSNs) is a collection of a large number of small, spatially distributed, and autonomous devices. These devices are known as sensor nodes. The Advancement in wireless communication leads to develop wireless sensor networks (WSN). It consists of small devices. These devices amass information by coordinating with each other. These tiny devices are known as a sensor node which consists of CPU (for data processing), memory (for data storage), battery (for energy) and transceiver (for receiving and sending signals or information from one node to further). The use of WSN is increasing day by day and at the same instance facing quandary of energy constraints in terms of short battery lifetime. Every node depends on the battery resource for assorted activities; this has becoming a most important concern in wireless sensor networks .so in this paper we are providing issues allied to sink repositioning that help to augment battery life time and also we provided information related to various approach for energy competent wsns.

scholarly journals A Data-Based Fault-Detection Model for Wireless Sensor Networks

2019 ◽  
Vol 11 (21) ◽  
pp. 6171 ◽  
Author(s):  
Jangsik Bae ◽  
Meonghun Lee ◽  
Changsun Shin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Detection ◽  
Data Transmission ◽  
Sensor Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensors And Actuators ◽  
Detection Model ◽  
Management Platform

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.

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