Deployment of multiple base-stations in clustering protocols of wireless sensor networks (WSNs)

2013 ◽  
Author(s):  
N. GouthamSekhar Reddy ◽  
Neeranjan Chitare ◽  
Srinivas Sampalli
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Base Stations ◽  
Wireless Sensor ◽  
Clustering Protocols

The Debris Flow Disaster Faster-Than-Early Forecast System (DFS) with Multi-Sensors Integrated Wireless Sensor Networks

2013 ◽  
Vol 347-350 ◽  
pp. 975-979
Author(s):  
Rong Zhao ◽  
Cai Hong Li ◽  
Yun Jian Tan ◽  
Jun Shi ◽  
Fu Qiang Mu ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Debris Flow ◽  
Real Time ◽  
Debris Flows ◽  
Base Station ◽  
Base Stations ◽  
Wireless Sensor ◽  
Forecast System ◽  
Debris Flow Disaster

This paper presents a Debris Flow Disaster Faster-than-early Forecast System (DFS) with wireless sensor networks. Debris flows carrying saturated solid materials in water flowing downslope often cause severe damage to the lives and properties in their path. Faster-than-early or faster-than-real-time forecasts are imperative to save lives and reduce damage. This paper presents a novel multi-sensor networks for monitoring debris flows. The main idea is to let these sensors drift with the debris flow, to collect flow information as they move along, and to transmit the collected data to base stations in real time. The Raw data are sent to the cloud processing center from the base station. And the processed data and the video of the debris flow are display on the remote PC. The design of the system address many challenging issues, including cost, deployment efforts, and fast reaction.

scholarly journals A SCALAR BASED ROUTING PROTOCOL APPLIED TO WIRELESS SENSOR NETWORKS

2021 ◽  
Vol 5 (12) ◽  
Author(s):  
Kailash Subramanian
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Power Supply ◽  
Routing Protocols ◽  
Base Station ◽  
Base Stations ◽  
Wireless Sensor ◽  
Efficient Manner ◽  
Failure Tolerance ◽  
Main Station

Wireless Sensor Networks motes have a small size, which leads to severe power supply restrictions. Much of the work on conserving power has been undertaken in the domain of routing protocols which deals with sending data in an efficient manner. In this paper a new scalar based protocol is proposed with a combination of multiple sub-base stations, that seeks to enhance the efficiency of protocol in terms of consumption of power and node failure tolerance. All the nodes are divided into regions, with each region having a sub- base station(sBS) and an arbitrary scalar value. Each sBS has lesser power supply and computation power compared to main station, but more of the mentioned metrics with respect to the sensor motes. Previous studies have described various paradigms and metrics for routing protocols and the placement of base stations. In this paper, the said algorithm is proposed, and its efficiency is analysed.

scholarly journals Proposed Intelligent Pre-Processing Model of Real-Time Flood Forecasting and Warning for Data Classification and Aggregation

2017 ◽  
Vol 13 (11) ◽  
pp. 4 ◽  
Author(s):  
Marouane El Mabrouk ◽  
Salma Gaou
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Real Time ◽  
Wireless Sensors ◽  
Data Classification ◽  
Flood Forecasting ◽  
Base Stations ◽  
Wireless Sensor ◽  
Time Data ◽  
Forecasting And Warning

A wireless sensor network is a network that can design a self-organizing structure and provides effective support for several protocols such as routing, locating, discovering services, etc. It is composed of several nodes called sensors grouped together into a network to communicate with each other and with the base stations. Nowadays, the use of Wireless sensor networks increased considerably. It can collect physical data and transform it into a digital values in real-time to monitor in a continuous manner different disaster like flood. However, due to various factors that can affect the wireless sensor networks namely, environmental, manufacturing errors hardware and software problems etc... It is necessary to carefully select and filter the data from the wireless sensors since we are providing a decision support system for flood forecasting and warning. In this paper, we presents an intelligent Pre-Processing model of real-time flood forecasting and warning for data classification and aggregation. The proposed model consists on several stages to monitor the wireless sensors and its proper functioning, to provide the most appropriate data received from the wireless sensor networks in order to guarantee the best accuracy in terms of real-time data and to generate a historical data to be used in the further flood forecasting.

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