 
								Implementation of Multisensor Data Fusion Algorithm
								
								
									
										Issue:
										Volume 5, Issue 4, August 2017
									
									
										Pages:
										48-53
									
								 
								
									Received:
										20 October 2017
									
									Accepted:
										1 November 2017
									
									Published:
										15 December 2017
									
								 
								
								
								
									
									
										Abstract: Multisensor data fusion is the process of combining observations from a number of different sensors to provide a robust and complete description of an environment or process of interest. Data fusion finds wide application in many areas of robotics such as object recognition, environment mapping, and localization. This work has three parts: methods, architectures and applications. Most current data fusion methods employ probabilistic descriptions of observations and processes and use Bayes’ rule to combine this information. Data fusion systems are often complex combinations of sensor devices, processing and fusion algorithms. This work provides an overview of key principles in data fusion architectures from both a hardware and algorithmic viewpoint. The applications of data fusion are pervasive in UAV and underlay the core problem of sensing, estimation and perception. The highlighted is many applications that bring out these features. The first describes a navigation or self-tracking application for an autonomous vehicle. The second describes an application in mapping and environment modeling. The essential algorithmic tools of data fusion are reasonably well established. However, the development and use of these tools in realistic robotics applications is still developing.
										Abstract: Multisensor data fusion is the process of combining observations from a number of different sensors to provide a robust and complete description of an environment or process of interest. Data fusion finds wide application in many areas of robotics such as object recognition, environment mapping, and localization. This work has three parts: methods,...
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								Gsm Based Low Cost Smart Irrigation System with Wireless Valve Control
								
									
										
											
											
												Saravanan Ragavan,
											
										
											
											
												Ramesh Thangavel
											
										
									
								 
								
									
										Issue:
										Volume 5, Issue 4, August 2017
									
									
										Pages:
										54-62
									
								 
								
									Received:
										23 October 2017
									
									Accepted:
										9 November 2017
									
									Published:
										22 December 2017
									
								 
								
								
								
									
									
										Abstract: In this paper presents to optimize the cost of the irrigation system and water consumption for agricultural crop based on a wireless network, that are Internet of Things (IoT) radio communications. The system consists of smart mobile phone for surveillance, the motor controller unit and the field controller unit. The SIM 900 GSM module is available in motor controller unit (PIC16F877A). Information from the field controller unit such as soil moisture, land humidity, temperature is sent to the motor controller unit through Radio & Communication. From motor controller unit the information is sent to the registered mobile number through GSM module. A Command can be sent from the mobile by GSM message to control the valves and motor.
										Abstract: In this paper presents to optimize the cost of the irrigation system and water consumption for agricultural crop based on a wireless network, that are Internet of Things (IoT) radio communications. The system consists of smart mobile phone for surveillance, the motor controller unit and the field controller unit. The SIM 900 GSM module is available...
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