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OPTIMAL SENSOR PLACEMENT AND VISUALIZATION SOFTWARE DEVELOPMENT *

OPTIMAL SENSOR PLACEMENT AND VISUALIZATION SOFTWARE DEVELOPMENT * Halil ÇAĞLAR & Serdar BÜYÜK & Aycan GÖKDEMİR Advisor :Doç. Dr. Osman PARLAKTUNA & Yrd. Doç. Dr. Ahmet YAZICI Eskişehir Osmangazi University Electrical-Electronics and Computer Engineering. Modelling of Environment.

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OPTIMAL SENSOR PLACEMENT AND VISUALIZATION SOFTWARE DEVELOPMENT *

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  1. OPTIMAL SENSOR PLACEMENT AND VISUALIZATION SOFTWARE DEVELOPMENT * Halil ÇAĞLAR & Serdar BÜYÜK & Aycan GÖKDEMİR Advisor :Doç. Dr. Osman PARLAKTUNA & Yrd. Doç. Dr. Ahmet YAZICIEskişehir Osmangazi University Electrical-Electronics and Computer Engineering Modelling of Environment Abstract The aim of this project is cover theall desired area with minimal sensor intersections. Every sensor cover a circular area. We are going to use some integrated development environments which are Matlab, Visual Studio especially C# and mapper. Mapper program allows to user draw plan of the room. Finally, time of the signal emitting from sensors will be represented with different color to clarify the emitting sensor to the user. Sensor Placement Approaches 1.Set covering The set-covering problem is an optimization problem that models many resource-selection problems. The goal is to cover all areas with minimum cost. Set covering model has objective function and constrains. Constrains change according to type of the problem. For example; base station placement problems have signal level constraint. Objective function: Min Z=c*x Constraints c :1xn (cost matrix) A*x ≥ e A: mxn (coverage matrix) x(j) ϵ {0,1} e: mx1 (all elements 1) • Firstly, the map of environment which is desired to placed sensor, is drawed with using Mapper program. Then mentioned map is loaded to program which is designed in this project. • Application Areas • Base Station Placement • Facility Location • Installation Network • Optimal Material Cutting 2.Genetic Algorithm A GeneticAlgorithm(GA) is a search heuristic that is process of natural evolution. The basic concept of GAs is designed to simulate processes in natural system necessary for evolution. This heuristic is routinely used to generateusefulsolutionsto optimization and search problems. Stages of Ga : Creation of a “;population” of strings, Evaluation of each string, Selection of best strings and Genetic manipulation to create new population of strings. Figure-4 Map of environment • Secondly, virtual grid is used to determine covered area by placed sensors. That virtual grid is shown in figure 5. User Interface User inteface which created using C# , is shown in the figure-7. Figure-1 Example of Base Station Placement Figure-5 Environment with Virtual grid • Finally, the sensors is placed with meta-heuristic and deterministic algorithm. The map of environment , Virtual grid and sensors are shown in figure 6. Figure-7 Graphical User Interface Results In this project, the sensor placement problem. is solved with two solution techniques. One of them is a type of deterministic other is a type of heuristic which are set covering and genetic algorithm. A user interface is also designed for the placement of sensors. Algorithms and the user interface can also be use to search optimal solutions for base stations placement, facility location and material cutting problems. Figure-2 Example of Facility Location Com. info: halilcaglar26@hotmail.com & sbuyuk88@hotmail.com & aycan.gkdmr@gmail.com Figure-6 Environment,virtual Grid and Placed Sensors *This project is supported by İnovasyon Mühendislik Figure-3 Example of Material Cutting

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