Sustainable data analysis framework of smart city based on wireless sensor network

2021 ◽  
Vol 25 (2) ◽  
pp. 114
Author(s):  
Hua Wang
Keyword(s):  
Data Analysis ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Smart City ◽  
Wireless Sensor ◽  
Analysis Framework

scholarly journals 3D GEO-CLUSTERING FOR WIRELESS SENSOR NETWORK IN SMART CITY

2019 ◽  
Vol XLII-4/W12 ◽  
pp. 11-16 ◽  
Author(s):  
S. Azri ◽  
U. Ujang ◽  
A. Abdul Rahman
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Smart City ◽  
Clustering Algorithm ◽  
Smart Cities ◽  
Wireless Sensor ◽  
Sensor Technology ◽  
Social Infrastructure ◽  
Head Node

<p><strong>Abstract.</strong> Smart city is a connection of physical and social infrastructure together with the information technology to leverage the collective intelligence of the city. Smart cities depend on a great extent on wireless sensor network to manage and maintain their services. Advanced sensor technologies are used to acquire information and help dealing with issues like air pollution, waste management, traffic optimization, and energy efficiency. However, no matter how much smart city may focus on sensor technology, data that are produced from sensors do not organize themselves in a database. Such tasks require a sophisticated database structure to produce informative data output. Besides that, wireless sensor network requires a proper design to improve the energy efficiency. The design will aid to prolong the lifespan of wireless network efficiently. In this study, we proposed a new technique that will be used to organize the information of wireless sensor network in the spatial database. Specific algorithm which is 3D geo-clustering algorithm is used to tackle several issues of location of the sensor in three-dimensional urban area in smart city. The algorithm is designed to minimizing the overlap among group clusters. Overlap plays an important role for energy efficiency. Thus, detection of sensors in two or more group clusters will avoid it from transmitting the same signal to cluster head node. It is prove that this algorithm would only create 5% to 10% overlap among group clusters. Several experiments are performed in this study to evaluate the algorithm. Based on the simulation results indicate that this algorithm can balance nodes energy consumption and prolong the network’s life span. It also has good stability and extensibility. Several tests are performed to validate the efficiency of the technique to measure the database performance.</p>

scholarly journals Essence of Scalability in Wireless Sensor Network for Smart City Applications

2021 ◽  
Vol 1022 ◽  
pp. 012094
Author(s):  
Roopali Dogra ◽  
Shalli Rani ◽  
Bhisham Sharma ◽  
Sandeep Verma
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Smart City ◽  
Wireless Sensor

scholarly journals Design of an Automatic Collision Avoidance System for Ships Based on Wireless Sensor Network

2018 ◽  
Vol 14 (05) ◽  
pp. 19
Author(s):  
Haohao Yuan
Keyword(s):  
Data Analysis ◽  
Wireless Sensor Network ◽  
Data Processing ◽  
Real Time ◽  
Sensor Network ◽  
Collision Avoidance ◽  
Wireless Sensor ◽  
Satellite Positioning ◽  
Collision Avoidance System ◽  
Information Collecting

The system designed is a ship collision avoidance system based on consistent use of satellite positioning technology, spread spectrum communication technology and a wireless sensor network. The system design includes: an information collecting terminal, a data processing terminal and a mobile data terminal as the three main parts. CC2530 is selected as the master chip for the information collecting terminal, and the GPS module with NEO-6M UBLOX satellite positioning function is used to obtain the latitude, longitude, heading and other information. The AS62-T30 wireless communication module is used to realize the data interaction between ships, and a 0.96-inch OLED display module is used to show the current location of the ship, thus realizing the GPS positioning data receiving, data analysis, information display, data integration and transmission, and other functions. In terms of the software in the data processing terminal, QT5 is selected as the development environment, and QtSql as the database to process and store the data packet sent by the information collecting terminal. The system has many functions including real-time data analysis and alarm, real-time location annotation, track query, route planning and weather forecasting, etc.

A privacy preserve big data analysis system for wearable wireless sensor network

2020 ◽  
Vol 96 ◽  
pp. 101887 ◽  
Author(s):  
Chunpeng Ge ◽  
Changchun Yin ◽  
Zhe Liu ◽  
Liming Fang ◽  
Juncen Zhu ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Big Data Analysis ◽  
Wireless Sensor ◽  
Privacy Preserve ◽  
Analysis System ◽  
Data Analysis System

scholarly journals Optimization and Simulation of Atmospheric Environment Monitoring System Based on Wireless Sensor

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zhenqiang Feng
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Monitoring System ◽  
Smart City ◽  
Monitoring Data ◽  
Atmospheric Environment ◽  
Wireless Sensor ◽  
Environment Monitoring ◽  
Virtual Force ◽  
Sensor Module

With the acceleration of urbanization, the problems in urban construction are becoming increasingly prominent, especially in air pollution. In order to deal with a series of problems brought by urbanization, the state has formulated the strategic layout of smart city construction. As an important measure and practice for the development of smart city, atmospheric environment monitoring is the premise of controlling atmospheric environment problems and plays a great role in environmental protection. The traditional automatic atmospheric environment monitoring station has complex structure, expensive price, and harsh working conditions, which is difficult to be popularized throughout the country. Aiming at the problems of poor expansibility and low intelligence of atmospheric environment monitoring system, an atmospheric environment monitoring system based on wireless sensor network is proposed. The system designs sensor module, networking module, gateway module, and monitoring interface, studies the accuracy of data collected by the system and the coverage of wireless sensor network, filters the environmental data collected by the sensor module, optimizes the layout of networking module by using improved virtual force algorithm, and finally tests the system. The experimental results show that the system realizes the remote monitoring of temperature, humidity, air pressure, and PM2.5 data, and the monitoring data is real and reliable. The improved virtual force algorithm improves the coverage of wireless sensor networks. Comparing the data collected by the system with the monitoring data of the cause control station, the average relative errors of PM2.5 and other particle parameters and NOx and other gas parameters monitored by the system are 3.81% and 3.48%, respectively; the system can be widely used in various environmental monitoring fields.

scholarly journals Dynamic Monitoring Of Agricultural Cultivation using IoT and Cloud Mechanism

2019 ◽  
Vol 8 (9) ◽  
pp. 556-560
Keyword(s):  
Data Analysis ◽  
Wireless Sensor Network ◽  
Internet Of Things ◽  
Sensor Network ◽  
Monitoring System ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Dynamic Monitoring ◽  
Wireless Sensor Nodes ◽  
Acquisition Strategies

The objective of this work is a dynamic monitoring of agricultural cultivation using WSN technology. The Wireless Sensor nodes are designed in controlling and supervising the factors of variegated of such as level of water, humidity, and temperature. ZigBee mechanism is used as a medium of transmission in WSN (Wireless Sensor Network) devices using sensors, routers which propagate the data to longer distance over a network, with the help of coordinator sensor and will transmit the data to the cloud computer, which in turn will illustrate the control and data in the monitoring system. The node sensor will extract the factors of agriculture from various sources on realtime and will transmit the data using IoT (Internet of Things), which is integrated with one another on various platforms for performing various types of actions and will reduce the need of labor. Apart from monitoring, enhancement of details can be proposed based on WSN for the deployment of various nodes and by applying digital acquisition strategies for acquisition of data and performing various types of data analysis on cloud using the collected information of agriculture

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