scholarly journals Distributed Fusion of Sensor Data in a Constrained Wireless Network

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1006 ◽  
Author(s):  
Charikleia Papatsimpa ◽  
Jean-Paul Linnartz
Keyword(s):  
Large Scale ◽  
Sensor Nodes ◽  
Sensor Data ◽  
A Posteriori ◽  
Likelihood Ratios ◽  
Process Data ◽  
Local Data ◽  
Fusion Algorithm ◽  
Distributed Information ◽  
Iot Devices

Smart buildings with connected lighting and sensors are likely to become one of the first large-scale applications of the Internet of Things (IoT). However, as the number of interconnected IoT devices is expected to rise exponentially, the amount of collected data will be enormous but highly redundant. Devices will be required to pre-process data locally or at least in their vicinity. Thus, local data fusion, subject to constraint communications will become necessary. In that sense, distributed architectures will become increasingly unavoidable. Anticipating this trend, this paper addresses the problem of presence detection in a building as a distributed sensing of a hidden Markov model (DS-HMM) with limitations on the communication. The key idea in our work is the use of a posteriori probabilities or likelihood ratios (LR) as an appropriate “interface” between heterogeneous sensors with different error profiles. We propose an efficient transmission policy, jointly with a fusion algorithm, to merge data from various HMMs running separately on all sensor nodes but with all the models observing the same Markovian process. To test the feasibility of our DS-HMM concept, a simple proof-of-concept prototype was used in a typical office environment. The experimental results show full functionality and validate the benefits. Our proposed scheme achieved high accuracy while reducing the communication requirements. The concept of DS-HMM and a posteriori probabilities as an interface is suitable for many other applications for distributed information fusion in wireless sensor networks.

Applications of Wireless Sensor Networks

2010 ◽  
pp. 1076-1090 ◽  
Author(s):  
Corinna Schmitt ◽  
Georg Carle
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Radio Communication ◽  
Power Resources ◽  
Limited Power

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.

scholarly journals An IoT-Based Network for Smart Urbanization

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Sabeeh Ahmad Saeed ◽  
Farrukh Zeeshan Khan ◽  
Zeshan Iqbal ◽  
Roobaea Alroobaea ◽  
Muneer Ahmad ◽  
...  
Keyword(s):  
Developing Countries ◽  
Data Structure ◽  
Internet Of Things ◽  
Information Exchange ◽  
Smart Cities ◽  
Sensor Nodes ◽  
Sink Node ◽  
Process Data ◽  
Data Format ◽  
Iot Devices

Internet of Things (IoT) is considered one of the world’s ruling technologies. Billions of IoT devices connected together through IoT forming smart cities. As the concept grows, it is very challenging to design an infrastructure that is capable of handling large number of devices and process data effectively in a smart city paradigm. This paper proposed a structure for smart cities. It is implemented using a lightweight easy to implement network design and a simpler data format for information exchange that is suitable for developing countries like Pakistan. Using MQTT as network protocol, different sensor nodes were deployed for collecting data from the environment. Environmental factors like temperature, moisture, humidity, and percentage of CO2 and methane gas were recorded and transferred to sink node for information sharing over the IoT cloud using an MQTT broker that can be accessed any time using Mosquitto client. The experiment results provide the performance analysis of the proposed network at different QoS levels for the MQTT protocol for IoT-based smart cities. JSON structure is used to formulate the communication data structure for the proposed system.

Efficient Multi-Level Human Motion Tracking Based on Compressive Infrared Sensing Paradigm

2013 ◽  
Vol 278-280 ◽  
pp. 988-993 ◽  
Author(s):  
Xiao Mu Luo ◽  
Dong Hui Liu ◽  
Hao Chen ◽  
Jia Ming Hong ◽  
Tong Liu ◽  
...  
Keyword(s):  
Motion Tracking ◽  
Large Scale ◽  
Human Motion ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Human Motion Tracking ◽  
Low Level ◽  
Infrared Sensing ◽  
Level Sensor ◽  
Multi Level

Multi-level human motion tracking and analysis is still an open question in person surveillance, especially with constrained computational and communication resources. In this paper, we propose a sensing paradigm which could address this challenge efficiently and effectively. The proposed paradigm mainly includes two components. First, we design a compressive infrared sensing model, which can sample and encode multi-level human motion into low-level sensor data directly, without the mediate process of scene recovery. Second, we employ lightweight data processing algorithms to detect and segment human motion at different levels, and decode the location information adaptively. We used self-developed pyroelectric infrared (PIR) sensor nodes to construct a wireless distributed network, and conducted experiments in real office environment. The experimental results showed that the proposed paradigm could track human motion at two levels robustly, and the computational and communication burden is low (5×1 sensor data stream at 5 Hz for processing). Our paradigm bridges the gap between the low-level sensor data and the high-level analysis for large-scale automated surveillance, and could serve as useful guidance for system design if needed.

scholarly journals MCEEP-BDA: Multilevel Clustering Based -Energy Efficient Privacy-Preserving Big Data Aggregation in Large-Scale Wsn

2019 ◽  
Vol 9 (1) ◽  
pp. 6779-6785
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Large Scale ◽  
Computational Cost ◽  
Privacy Preserving ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Communication Overhead

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.

scholarly journals Approach in the development of lightweight microservice architecture for small data center monitoring system

2020 ◽  
Vol 3 (2) ◽  
Author(s):  
Milan Malić ◽  
Dalibor Dobrilović ◽  
Dušan Malić ◽  
Željko Stojanov
Keyword(s):  
Software Architecture ◽  
Real Time ◽  
Data Center ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Small Data ◽  
Test Results ◽  
Iot Devices ◽  
Sqlite Database ◽  
Microservice Architecture

In the past decade there is a significant trend of implementing IoT technologies and standards in different industries. This trend brings cost reductions to the companies and other benefits as well. One of the main benefits is real-time and uniform data collection. The data are transferred using diverse communication protocols, from the sensor nodes to the centralized application. So far, current approaches in developing applications are not proved itself to be efficient enough in scenarios when a significant amount of data needs to be stored and analyzed. The focus of this paper is on development of software architecture suitable for usage in Internet of Things (IoT) systems where the larger amount of data can be processed in real-time. The software architecture is developed in order to support the sensor network for monitoring the small data center and it is based on microservices. Besides the system and its architecture, this paper presents the method of analysis of system performances in real-time environment. The proposal for lightweight microservice architecture, presented in this paper, is developed with .NET Core and RabbitMQ, with the utilization of MongoDB and SQLite databases systems for storing data collected with IoT devices. In this paper, the system evaluation and research results in different stress scenarios are also presented. Because of its complexity, only the most significant segments of architecture will be presented in this paper. The proposed solution showed that proposed lightweight architecture based on microservices could deal with the larger amount of sensor data in the case of using MongoDB. On the other hand, the usage of SQLite database is not recommended due to the lower performances and test results.

scholarly journals Architecture of an MAS-Based Intelligent Communication in a WSN

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Mostefa Bendjima ◽  
Mohammed Feham
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Large Scale ◽  
Data Transfer ◽  
Base Station ◽  
Sensor Nodes ◽  
Process Data ◽  
Communication Architecture ◽  
Efficient Data ◽  
Intelligent Communication

Wireless sensor networks (WSNs) are designed to collect information across a large number of sensor nodes with limited batteries. Therefore, it is important to minimize energy consumption of each node, so as to extend the lifetime of the network. This paper proposes the use of an intelligent WSN communication architecture based on a multiagent system (MAS), to ensure optimal data collection. MAS refers to a group of agents that interact and cooperate to achieve a specific goal. To ensure this objective, we propose the integration of a migrating agent into each node to process data and enhance cooperation between neighboring nodes, while mobile agents (MAs) can be used to reduce data transfer between the nodes and send them to the base station (Sink). The collaboration of these agents generates a simple message that summarizes important information to be transmitted by an MA. To reduce the size of MAs, nodes in the network sectors are grouped in such way that, for each MA, an optimal itinerary is established, using a minimum amount of energy with efficient data aggregation within a minimum time. Successive simulations in large-scale sensor networks show the good performance of our proposal in terms of energy consumption and packet delivery rate.

An Adaptive Data Dissemination Strategy for Wireless Sensor Networks

2007 ◽  
Vol 3 (1) ◽  
pp. 23-40 ◽  
Author(s):  
S. Selvakennedy ◽  
S. Sinnappan
Keyword(s):  
Sensor Networks ◽  
Energy Dissipation ◽  
Large Scale ◽  
Clustering Algorithm ◽  
Data Dissemination ◽  
Discrete Event ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Energy Awareness ◽  
Communication Task

Future large-scale sensor networks may comprise thousands of wirelessly connected sensor nodes that could provide an unimaginable opportunity to interact with physical phenomena in real time. However, the nodes are typically highly resource-constrained. Since the communication task is a significant power consumer, various attempts have been made to introduce energy-awareness at different levels within the communication stack. Clustering is one such attempt to control energy dissipation for sensor data dissemination in a multihop fashion. The Time-Controlled Clustering Algorithm (TCCA) is proposed to realize a network-wide energy reduction. A realistic energy dissipation model is derived probabilistically to quantify the sensor network's energy consumption using the proposed clustering algorithm. A discrete-event simulator is developed to verify the mathematical model and to further investigate TCCA in other scenarios. The simulator is also extended to include the rest of the communication stack to allow a comprehensive evaluation of the proposed algorithm.

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
Keyword(s):  
Monitoring System ◽  
Data Storage ◽  
Large Scale ◽  
Nonlinear Problems ◽  
Original Data ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Mine Environment ◽  
Multi Sensor Data Fusion

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.

scholarly journals Development of an IoT based Air Quality Monitoring System

2019 ◽  
Vol 8 (10S) ◽  
pp. 23-28
Keyword(s):  
Air Quality ◽  
Web Application ◽  
Large Scale ◽  
Environmental Parameters ◽  
Air Pollutant ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Quality Data ◽  
Indoor Environments ◽  
Http Protocol

The proposed work aims for a large-scale air pollutant monitoring for ambient and indoor environments. This system is developed to measure various environmental parameters. Sourceof pollutants can be identified by analyzing the data collected from the various sensor nodes, so that air quality can be monitored by applying engineering science and data. This is achieved by installing multiple sensor stations in various locations such as hospitals, factories, Offices, streets and weather stations. These sensor stations measure the environmental parameters such as PM2.5, PM10, Sulphate (SOx), Nitrate (NOx), Ozone(O3), Volatile Organic Compounds (VOC), Temperature and Humidity. The sensor stations communicate with cloud over HTTP protocol. Each station has ESP 8266 smart controller which captures the sensor data and creates forms theJavaScript Object Notation (JSON) data packets that mainly consists of sensor data along with node address. These packets will be sent to the cloud over HTTP protocol. The user can access the air quality data from the web application.

Open Lorawan Sensor Node Architecture for Agriculture Applications

2021 ◽  
Author(s):  
Philipp Bolte ◽  
Ulf Witkowski ◽  
Rolf Morgenstern
Keyword(s):  
Sensor Node ◽  
Large Scale ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Wireless Sensor Node ◽  
Wireless Data ◽  
Wireless Data Transmission ◽  
Power Battery ◽  
New Sensors

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.

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