Intelligent Industrial Data Acquisition and Energy Monitoring using Wireless Sensor Networks

2010 ◽  
Vol 2 (3) ◽  
pp. 44-59 ◽  
Author(s):  
Sumeet Gupta ◽  
Shekhar Verma ◽  
G.S. Tomar ◽  
Raj Kumar Abrol

Most of the application-oriented research in the field of Wireless Sensor Networks has been in remote monitoring, including environmental, building automation, and security. However, this paper presents the methodology followed for implementation of a Wireless Sensor Network based solution in a process plant for energy management and leak detection. The sensor network acquires data pertaining to detection of leakage in a plant. The network further serves effectively as a maintenance and diagnostic system that is used to manage the plant and conserve energy in a process plant. The critical design issues, testing methodologies and implementation problems pertaining to the system are also presented. Additionally, special focus has been placed on the calculations pertaining to the network life time.

Author(s):  
Sumeet Gupta ◽  
Shekhar Verma ◽  
G.S. Tomar ◽  
Raj Kumar Abrol

Most of the application-oriented research in the field of Wireless Sensor Networks has been in remote monitoring, including environmental, building automation, and security. However, this paper presents the methodology followed for implementation of a Wireless Sensor Network based solution in a process plant for energy management and leak detection. The sensor network acquires data pertaining to detection of leakage in a plant. The network further serves effectively as a maintenance and diagnostic system that is used to manage the plant and conserve energy in a process plant. The critical design issues, testing methodologies and implementation problems pertaining to the system are also presented. Additionally, special focus has been placed on the calculations pertaining to the network life time.


Author(s):  
Wajeeha Aslam ◽  
Muazzam A. Khan ◽  
M. Usman Akram ◽  
Nazar Abbas Saqib ◽  
Seungmin Rho

Wireless sensor networks are greatly habituated in widespread applications but still yet step behind human intelligence and vision. The main reason is constraints of processing, energy consumptions and communication of image data over the sensor nodes. Wireless sensor network is a cooperative network of nodes called motes. Image compression and transmission over a wide ranged sensor network is an emerging challenge with respect to battery, life time constraints. It reduces communication latency and makes sensor network efficient with respect to energy consumption. In this paper we will have an analysis and comparative look on different image compression techniques in order to reduce computational load, memory requirements and enhance coding speed and image quality. Along with compression, different transmission methods will be discussed and analyzed with respect to energy consumption for better performance in wireless sensor networks.


2019 ◽  
Vol 8 (4) ◽  
pp. 8666-8672

Today we can’t think communication systems without support of advancements made in computer technologies whereby it is a major achievement to realize the convergence of the technologies providing highly pervasive system. The communication systems evolved essentially from wired communications and grew to the current wireless communications. Wireless sensor networks do not need large deployment infrastructure. Here each individual sensor node acts as a part of the overall infrastructure. All nodes are connected in multi-hop mesh topology. In this flexible mesh architecture, we easily add new nodes and scale up to achieve control and monitoring over larger region. The sensor network protocols and algorithms possess self-organizing capabilities. Wireless sensor network communication systems mostly being deployed in open fields are physically accessible to adversaries and are more vulnerable due to being remotely managed, densely deployed, low power (battery life time), low communication bandwidth, low processing capability, and use of only the broadcasting mechanism to communicate with other nodes[1].


Author(s):  
Md. Navid Bin Anwar ◽  
Maherin Mizan Maha

Wireless sensor network (WSN) is a group of several autonomous sensor nodes attached to each other. Wireless sensor networks are commonly used in a lot of applications and are expected to have a cheap deployment cost. The network of sensors continues to grow aiding the need of the system. Due to that, sensors become vulnerable to attacks and need strong security mechanism. To strengthen the security of data which are transmitted through sensors in WSN, different cryptographic schemes are used. As WSN has limited energy source, therefore, complex cryptographic algorithms may require excessive computational time which not only make the data transmission slow but the life time of sensor network will be significantly affected. To overcome these challenges a new hybrid cryptographic scheme, AES and Modified Playfair Cipher (AMPC), is introduced in this paper.


2021 ◽  
Author(s):  
Swapna Ch ◽  
Vijayashree R Budyal

Abstract The most challenging task in wireless sensor network is energy efficiency, as energy is the major constraint in the wireless sensor network to improve the life time of the network. Hence developing algorithms to improve network life time is the major task. In wireless sensor network most of the energy is wasted while gathering the data, hence an efficient algorithm which conserves energy has to be designed. Thus our proposed work A Novel Data Gathering Algorithm for Wireless Sensor Networks using Artificial Intelligence (NDGAI) uses mobile element and deals with the conservation of energy while gathering the data. Appropriate clustering, cluster leader selection and proper path determination of mobile element helps to conserve energy and improve the over all network life time. In our proposed work initially the clusters are forged by using Amended Expectation Maximization(AEM) algorithm, which is the maximum likelihood estimate. It is used along with Gap statistic method to find the optimal number of clusters. AEM algorithm helps in obtaining the centres of the cluster with maximum number of nodes near the cluster centres. For each cluster, Cluster Leader (CL) is selected by using Fuzzy Logic. Fuzzy logic selects the node which is near to the cluster centre by using parameters such as Closeness of node to the Cluster Centroid, direction of node towards base station, number of Neighbouring Nodes. After the CL’s are determined, to reduce the path length virtual points(VP) are selected so that mobile element reaches this virtual point and collects the data. These VP’s are selected only when the CL has data in it. The mobile elements can reach these virtual points intelligently by using optimal path,that is obtained by using hybrid of Particle Swarm Optimization and Artificial Bee Colony algorithm. Thus the mobile element travels in the optimal path and gathers the data from the entire network intelligently and efficiently with less amount of energy. With this approach the performance and life time of the network is improved while gathering the data. The simulation results are compared with Scalable Grid-Based Data Gathering Algorithm for Environmental Monitoring Wireless Sensor Networks (SGBDN) and proved that the proposed method is better than SGBDN .


Author(s):  
Omkar Singh ◽  
Vinay Rishiwal

Background & Objective: Wireless Sensor Network (WSN) consist of huge number of tiny senor nodes. WSN collects environmental data and sends to the base station through multi-hop wireless communication. QoS is the salient aspect in wireless sensor networks that satisfies end-to-end QoS requirement on different parameters such as energy, network lifetime, packets delivery ratio and delay. Among them Energy consumption is the most important and challenging factor in WSN, since the senor nodes are made by battery reserved that tends towards life time of sensor networks. Methods: In this work an Improve-Energy Aware Multi-hop Multi-path Hierarchy (I-EAMMH) QoS based routing approach has been proposed and evaluated that reduces energy consumption and delivers data packets within time by selecting optimum cost path among discovered routes which extends network life time. Results and Conclusion: Simulation has been done in MATLAB on varying number of rounds 400- 2000 to checked the performance of proposed approach. I-EAMMH is compared with existing routing protocols namely EAMMH and LEACH and performs better in terms of end-to-end-delay, packet delivery ratio, as well as reduces the energy consumption 13%-19% and prolongs network lifetime 9%- 14%.


2018 ◽  
Vol 7 (2.26) ◽  
pp. 25
Author(s):  
E Ramya ◽  
R Gobinath

Data mining plays an important role in analysis of data in modern sensor networks. A sensor network is greatly constrained by the various challenges facing a modern Wireless Sensor Network. This survey paper focuses on basic idea about the algorithms and measurements taken by the Researchers in the area of Wireless Sensor Network with Health Care. This survey also catego-ries various constraints in Wireless Body Area Sensor Networks data and finds the best suitable techniques for analysing the Sensor Data. Due to resource constraints and dynamic topology, the quality of service is facing a challenging issue in Wireless Sensor Networks. In this paper, we review the quality of service parameters with respect to protocols, algorithms and Simulations. 


2017 ◽  
Vol 13 (05) ◽  
pp. 122 ◽  
Author(s):  
Bo Feng ◽  
Wei Tang ◽  
Guofa Guo

In wireless sensor networks, the nodes around the base station have higher energy consumption due to the forwarding task of all the detected data. In order to balance the energy consumption of the nodes around the base station, a reasonable and effective mechanism of node rotation dormancy is put forward. In this way, a large number of redundant nodes in the network are in a dormant state, so as to reduce the load of important nodes around the base station. The problems of the redundant nodes in the sensor network are analyzed, and a new method is proposed to distinguish the redundant nodes based on local Delaunay triangulation and multi node election dormancy mechanism. The experimental results showed that this method could effectively distinguish the redundant nodes in the network; at the same time, through the multi round election mechanism, parts of redundant nodes are made dormant. In summary, they can reduce the network energy consumption on the condition of guaranteeing the original coverage.


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