Wireless Sensor
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2021 ◽  
Vol 2021 ◽  
pp. 1-14
Felicia Engmann ◽  
Kofi Sarpong Adu-Manu ◽  
Jamal-Deen Abdulai ◽  
Ferdinand Apietu Katsriku

In Wireless Sensor Networks, sensor nodes are deployed to ensure continuous monitoring of the environment which requires high energy utilization during the data transmission. To address the challenge of high energy consumption through frequent independent data transmission, the IEEE 802.11b provides a backoff window that reduces collisions and energy losses. In the case of Internet of Things (IoTs), billions of devices communicate with each other simultaneously. Therefore, adapting the contention/backoff window size to data traffic to reduce congestion has been one such approach in WSN. In recent years, the IEEE 802.11b MAC protocol is used in most ubiquitous technology adopted for devices communicating in the IoT environment. In this paper, we perform a thorough evaluation of the IEEE 802.11b standard taking into consideration the channel characteristics for IoT devices. Our evaluation is aimed at determining the optimum parameters suitable for network optimization in IoT systems utilizing the IEEE 802.11b protocol. Performance analysis is made on the sensitivity of the IEEE 802.11b protocol with respect to the packet size, packet delivery ratio (PDR), end-to-end delay, and energy consumption. Our studies have shown that for optimal performance, IoT devices using IEEE 802.11b channel require data packet of size 64 bytes, a data rate of 11Mbps, and an interpacket generation interval of 4 seconds. The sensitivity analysis of the optimal parameters was simulated using NS3. We observed PDR values ranging between 27% and 31%, an average end-to-end delay ranging within 10-15 ms while the energy remaining was between 5.59 and 5.63Joules. The results clearly indicate that scheduling the rate of packet generation and transmission will improve the network performance for IoT devices while maintaining data reliability.

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Lin Feng ◽  
Jian Wang ◽  
Ye Chen ◽  
Chao Ding

This paper studies a semiconductor wireless sensor system, which is composed of a semiconductor wireless sensor sampling circuit, gas-sensitive signal alarm and wireless transmitting circuit, and wireless radio frequency signal receiving circuit. The system is suitable for wireless monitoring of hydrogen fluoride gas in chemical plants. The hydrogen fluoride gas sensor is designed, integrated, and classified according to the polarity and size of the sensor output signal. The signal processing circuit of the sensor output signal is made with an integrated design. This paper developed a simulation experimental system for the wireless monitoring network characteristics of toxic hydrogen fluoride gas and completed the monitoring system’s sensor characteristic calibration and accuracy comparison simulation experiment, the communication distance test experiment of the communication system, and the research experiment on the influence of environmental humidity on the sensor characteristics of the monitoring system. In terms of software, the workflow of network nodes has been optimized. Since the structure of the wireless sensor network is not exactly the same in different application fields, the toxic gas monitoring system based on wireless sensor networks must focus on extending the network’s life cycle. Without affecting the normal operation of the system, distributed compressed sensing can greatly extend the service life of the system. Therefore, this subject combines the compressed sensing technology developed in recent years with the air monitoring system for the processing of transmission data, in order to achieve the purpose of further reducing the energy consumption of the system. The simulation experiment demonstrated that the lmF neural network combined with gas sensor array technology can realize qualitative identification, quantitative analysis of single gas, and quantitative analysis of mixed combustible gas. The research work in this area also provides a new way to further combine the miniature hydrogen fluoride gas sensor unit with sensor technology, integrate the hydrogen fluoride gas sensor unit and the electronic tag, and expand the wireless application of the gas sensor.

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Yan Lv ◽  
Laijun Lu

In order to mine geological mineral energy and study on geological mineral energy classification, a method based on a wireless sensor was proposed. Of logistic regression, artificial neural networks, random forests, and main wireless sensor algorithms of support vector machine (SVM) with the model in the application of the energy mineral resource prediction practice effects are reviewed and discuss the practical application in the process of sample selection, the wrong points existing in the cost, the uncertainty evaluation, and performance evaluation of the model using wireless sensor algorithm, random forest of the probability distribution of mineralization in the study area is calculated, and five prospecting potential areas are delineated. The results show that the ratio of ore-bearing unit and non-ore-bearing unit is 1 : 1, and the best random forest training model is obtained. 70% of the training sample set was randomly selected as the training set, and the remaining 30% was used as the test set to construct the random forest model. The training accuracy of the model is 96.7%, and the testing accuracy is 96.5%. Both model training accuracy and model testing accuracy are very high, which proves the accuracy of RF model construction and achieves satisfactory results. In this study, a wireless sensor is successfully applied to 3D mineral energy prediction, which makes a positive exploration for mineral resource prediction and evaluation in the future. Finally, the prediction of mineral resource energy based on a wireless sensor is an important trend of future development.

2021 ◽  
Vol 10 (4) ◽  
pp. 1-13
Idrees Sarhan Kocher

Wireless Sensor Networks (WSN) is now an evolving technology and has a broad range of applications, such as battlefield surveillance, traffic surveillance, detection of forest fires, detection of floods, etc. The communication nature of the wireless sensor network is unprotected and dangerous due to deployment in hostile environments, restricted resources, an automatic nature, and untrusted media for broadcast transmission. For wireless sensor networks, several routing protocols have been suggested, but none of them have been developed with protection as a target. The majority function in routing algorithms currently in place for sensor networks optimize a restricted capacities in sensor nodes and the application based design of WSNs. A WSNs, however, are exposed to a number of possible threats that impede the network's regular activity. Thus, there is a strong need to provide the routing protocols of the OSI structure layer with a safe mechanism to prevent an attacker from obstructing it.   The well-known attacks against all layers are discussed in this systematic roadmap, and debilitating attacks against routing protocols are analyzed and defined in particular. Several suggested attack countermeasures, design considerations and paper contributions are also included in the routing protocols. The assertion of the study is that WSN routing protocols must be built with protection in mind, and this is the only efficient solution in WSNs for safe routing. The aim of this paper is also to provide problems, attacks and countermeasures related to protection. Finally, it is hoped that this roadmap would inspire potential researchers to come up with smarter and better protection measures and make their network safer. The first such research analysis of secure routing protocols in WSNs is this roadmap study.

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