Study of Mine Environment Monitoring System Based on Wireless Sensor Network

2013 ◽  
Vol 278-280 ◽  
pp. 809-812
Author(s):  
Jun Wang ◽  
Feng Wang ◽  
Shu Ren Han

There are a large number of sensors to detect information in mine environment system, which provides the original data for the prevention and treatment of mine accidents. According to data flow of data acquisition, data transmission, data storage and data processing, this paper used CC2530 to design the wireless sensor nodes, analyzed the Zigbee network topology underground and designed an optimized PEGASIS protocol. The multi-sensor data fusion method was applied to the multi-parameter and large-scale mine data, solved the nonlinear problems in the multi-feature selection and extraction and also improved the performance of mine monitoring system.

Author(s):  
Corinna Schmitt ◽  
Georg Carle

Today the researchers want to collect as much data as possible from different locations for monitoring reasons. In this context large-scale wireless sensor networks are becoming an active topic of research (Kahn1999). Because of the different locations and environments in which these sensor networks can be used, specific requirements for the hardware apply. The hardware of the sensor nodes must be robust, provide sufficient storage and communication capabilities, and get along with limited power resources. Sensor nodes such as the Berkeley-Mote Family (Polastre2006, Schmitt2006) are capable of meeting these requirements. These sensor nodes are small and light devices with radio communication and the capability for collecting sensor data. In this chapter the authors review the key elements for sensor networks and give an overview on possible applications in the field of monitoring.


In current scenario, the Big Data processing that includes data storage, aggregation, transmission and evaluation has attained more attraction from researchers, since there is an enormous data produced by the sensing nodes of large-scale Wireless Sensor Networks (WSNs). Concerning the energy efficiency and the privacy conservation needs of WSNs in big data aggregation and processing, this paper develops a novel model called Multilevel Clustering based- Energy Efficient Privacy-preserving Big Data Aggregation (MCEEP-BDA). Initially, based on the pre-defined structure of gradient topology, the sensor nodes are framed into clusters. Further, the sensed information collected from each sensor node is altered with respect to the privacy preserving model obtained from their corresponding sinks. The Energy model has been defined for determining the efficient energy consumption in the overall process of big data aggregation in WSN. Moreover, Cluster_head Rotation process has been incorporated for effectively reducing the communication overhead and computational cost. Additionally, algorithm has been framed for Least BDA Tree for aggregating the big sensor data through the selected cluster heads effectively. The simulation results show that the developed MCEEP-BDA model is more scalable and energy efficient. And, it shows that the Big Data Aggregation (BDA) has been performed here with reduced resource utilization and secure manner by the privacy preserving model, further satisfying the security concerns of the developing application-oriented needs.


2013 ◽  
Vol 64 (3) ◽  
Author(s):  
Nurul Mu’azzah Abdul Latiff ◽  
Mohd Musa Mohamad ◽  
Sharifah Kamilah Syed Yusof ◽  
, Mohd. Rozaini Abd. Rahim ◽  
Hamdan Sayuti ◽  
...  

Recently, technological advance in Android application has grown rapidly especially in health care application along with the development of smartphone. The utilization of wireless sensor networks with the mobile wireless health devices has provided us with an alternative solution in health monitoring instead of using the traditional approach with higher cost. Therefore, the objective of this project is to develop and implement a training monitoring system for cyclist based on android application. In this system, wireless sensor nodes are assigned to collect the required data such as cyclist’s heart rate and cadence. All the data are then sent to the mobile device used by cyclist via wireless communication. The data collected are first stored in device’s internal memory before they are transferred to the server. This project involved programming of hardware using specific software such as Eclipse Juno Android SDK and SQLite database. The system also includes the graphical user interface (GUI) design using Java language for application on smartphone. In addition, the simple Dropbox command is used to design the server for data storage. All the stages of implementations are integrated in one whole system and can be run as an application by cyclist. The developed system is proven to be cost effective and reliable as well as easy for customization.


2021 ◽  
Author(s):  
Philipp Bolte ◽  
Ulf Witkowski ◽  
Rolf Morgenstern

In agriculture, it becomes more and more important to have detailed data, e.g. about weather and soil quality, not only in large scale classic crop farming applications but also for urban agriculture. This paper proposes a modular wireless sensor node that can be used in a centralized data acquisition scenario. A centralized approach, in this case multiple sensor nodes and a single gateway or a set of gateways, can be easily installed even without local infrastructure as mains supply. The sensor node integrates a LoRaWAN radio module that allows long-range wireless data transmission and low-power battery operation for several months at reasonable module costs. The developed wireless sensor node is an open system with focus on easy adaption to new sensors and applications. The proposed system is evaluated in terms of transmission range, battery runtime and sensor data accuracy.


2018 ◽  
Vol 14 (01) ◽  
pp. 4
Author(s):  
Wang Weidong

To improve the efficiency of the remote monitoring system for logistics transportation, we proposed a remote monitoring system based on wireless sensor network and GPRS communication. The system can collect information from the wireless sensor network and transmit the information to the ZigBee interpreter. The monitoring system mainly includes the following parts: Car terminal, GPRS transmission network and monitoring center. Car terminal mainly consists by the Zigbee microcontroller and peripherals, wireless sensor nodes, RFID reader, GPRS wireless communication module composed of a micro-wireless monitoring network. The information collected by the sensor communicates through the GPRS and the monitoring center on the network coordinator, sends the collected information to the monitoring center, and the monitoring center realizes the information of the logistics vehicle in real time. The system has high applicability, meets the design requirements in the real-time acquisition and information transmission of the information of the logistics transport vehicles and goods, and realizes the function of remote monitoring.


Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 218
Author(s):  
Ala’ Khalifeh ◽  
Khalid A. Darabkh ◽  
Ahmad M. Khasawneh ◽  
Issa Alqaisieh ◽  
Mohammad Salameh ◽  
...  

The advent of various wireless technologies has paved the way for the realization of new infrastructures and applications for smart cities. Wireless Sensor Networks (WSNs) are one of the most important among these technologies. WSNs are widely used in various applications in our daily lives. Due to their cost effectiveness and rapid deployment, WSNs can be used for securing smart cities by providing remote monitoring and sensing for many critical scenarios including hostile environments, battlefields, or areas subject to natural disasters such as earthquakes, volcano eruptions, and floods or to large-scale accidents such as nuclear plants explosions or chemical plumes. The purpose of this paper is to propose a new framework where WSNs are adopted for remote sensing and monitoring in smart city applications. We propose using Unmanned Aerial Vehicles to act as a data mule to offload the sensor nodes and transfer the monitoring data securely to the remote control center for further analysis and decision making. Furthermore, the paper provides insight about implementation challenges in the realization of the proposed framework. In addition, the paper provides an experimental evaluation of the proposed design in outdoor environments, in the presence of different types of obstacles, common to typical outdoor fields. The experimental evaluation revealed several inconsistencies between the performance metrics advertised in the hardware-specific data-sheets. In particular, we found mismatches between the advertised coverage distance and signal strength with our experimental measurements. Therefore, it is crucial that network designers and developers conduct field tests and device performance assessment before designing and implementing the WSN for application in a real field setting.


Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 219
Author(s):  
Phuoc Duc Nguyen ◽  
Lok-won Kim

People nowadays are entering an era of rapid evolution due to the generation of massive amounts of data. Such information is produced with an enormous contribution from the use of billions of sensing devices equipped with in situ signal processing and communication capabilities which form wireless sensor networks (WSNs). As the number of small devices connected to the Internet is higher than 50 billion, the Internet of Things (IoT) devices focus on sensing accuracy, communication efficiency, and low power consumption because IoT device deployment is mainly for correct information acquisition, remote node accessing, and longer-term operation with lower battery changing requirements. Thus, recently, there have been rich activities for original research in these domains. Various sensors used by processing devices can be heterogeneous or homogeneous. Since the devices are primarily expected to operate independently in an autonomous manner, the abilities of connection, communication, and ambient energy scavenging play significant roles, especially in a large-scale deployment. This paper classifies wireless sensor nodes into two major categories based the types of the sensor array (heterogeneous/homogeneous). It also emphasizes on the utilization of ad hoc networking and energy harvesting mechanisms as a fundamental cornerstone to building a self-governing, sustainable, and perpetually-operated sensor system. We review systems representative of each category and depict trends in system development.


Author(s):  
Osman Salem ◽  
Alexey Guerassimov ◽  
Ahmed Mehaoua ◽  
Anthony Marcus ◽  
Borko Furht

This paper details the architecture and describes the preliminary experimentation with the proposed framework for anomaly detection in medical wireless body area networks for ubiquitous patient and healthcare monitoring. The architecture integrates novel data mining and machine learning algorithms with modern sensor fusion techniques. Knowing wireless sensor networks are prone to failures resulting from their limitations (i.e. limited energy resources and computational power), using this framework, the authors can distinguish between irregular variations in the physiological parameters of the monitored patient and faulty sensor data, to ensure reliable operations and real time global monitoring from smart devices. Sensor nodes are used to measure characteristics of the patient and the sensed data is stored on the local processing unit. Authorized users may access this patient data remotely as long as they maintain connectivity with their application enabled smart device. Anomalous or faulty measurement data resulting from damaged sensor nodes or caused by malicious external parties may lead to misdiagnosis or even death for patients. The authors' application uses a Support Vector Machine to classify abnormal instances in the incoming sensor data. If found, the authors apply a periodically rebuilt, regressive prediction model to the abnormal instance and determine if the patient is entering a critical state or if a sensor is reporting faulty readings. Using real patient data in our experiments, the results validate the robustness of our proposed framework. The authors further discuss the experimental analysis with the proposed approach which shows that it is quickly able to identify sensor anomalies and compared with several other algorithms, it maintains a higher true positive and lower false negative rate.


2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881130 ◽  
Author(s):  
Jaanus Kaugerand ◽  
Johannes Ehala ◽  
Leo Mõtus ◽  
Jürgo-Sören Preden

This article introduces a time-selective strategy for enhancing temporal consistency of input data for multi-sensor data fusion for in-network data processing in ad hoc wireless sensor networks. Detecting and handling complex time-variable (real-time) situations require methodical consideration of temporal aspects, especially in ad hoc wireless sensor network with distributed asynchronous and autonomous nodes. For example, assigning processing intervals of network nodes, defining validity and simultaneity requirements for data items, determining the size of memory required for buffering the data streams produced by ad hoc nodes and other relevant aspects. The data streams produced periodically and sometimes intermittently by sensor nodes arrive to the fusion nodes with variable delays, which results in sporadic temporal order of inputs. Using data from individual nodes in the order of arrival (i.e. freshest data first) does not, in all cases, yield the optimal results in terms of data temporal consistency and fusion accuracy. We propose time-selective data fusion strategy, which combines temporal alignment, temporal constraints and a method for computing delay of sensor readings, to allow fusion node to select the temporally compatible data from received streams. A real-world experiment (moving vehicles in urban environment) for validation of the strategy demonstrates significant improvement of the accuracy of fusion results.


2018 ◽  
Vol 14 (8) ◽  
pp. 155014771879584 ◽  
Author(s):  
Danyang Qin ◽  
Yan Zhang ◽  
Jingya Ma ◽  
Ping Ji ◽  
Pan Feng

Due to the advantages of large-scale, data-centric and wide application, wireless sensor networks have been widely used in nowadays society. From the physical layer to the application layer, the multiply increasing information makes the data aggregation technology particularly important for wireless sensor network. Data aggregation technology can extract useful information from the network and reduce the network load, but will increase the network delay. The non-exchangeable feature of the battery of sensor nodes makes the researches on the battery power saving and lifetime extension be carried out extensively. Aiming at the delay problem caused by sleeping mechanism used for energy saving, a Distributed Collision-Free Data Aggregation Scheme is proposed in this article to make the network aggregate data without conflicts during the working states periodically changing so as to save the limited energy and reduce the network delay at the same time. Simulation results verify the better aggregating performance of Distributed Collision-Free Data Aggregation Scheme than other traditional data aggregation mechanisms.


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