16337

14573

كارشناسي ارشد

كنترل

اصفهان : دانشگاه صنعتي اصفهان

1399

هشت، 81ص. : مصور، جدول، نمودار

جعفر قيصري

احسان يزديان

ايمان ايزدي، فريد شيخ‌الاسلام

1399/12/12

كتابنامه

مهندسي برق

مهندسي برق و كامپيوتر

1399/12/13

2602695

Event Detection Using Compressive Sensing for Data Estimation and Implementation in Flood Detection Fatemeh Zarei Jalal abadi May 2020 Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Dr Jafar Ghaisari Advisor Dr Ehsan YazdianAbstract Wireless sensor networks WSN consist of numerous nodes that responsible for sensing processing andmonitoring of physical environment data and have been widely used nowadays In WSN there are limitations such as hugeamounts of data and limited power source therefore using some methods to reduce amounts of data and power consumptionis very important also data may be lost in WSN and not be received by the receiver for different reasons In this thesis twomethods of compressive sensing and matrix completion are proposed to reduce the amount of data Distributed compressivesensing is used to benefit spatial correlation in addition to temporal correlation of data The accuracy of reconstruction ofthese methods is compared with the same compression percentage Then a flood detection has done with level and flowwater of rivers data from 2013 Canada flooding In this simulation fuzzy logic has been used as a determinant of theconditions that is safe prone and danger Then it is assumed that the data may be missed by probability of 10 percent Inthis regard a real time method compressive sensing based for estimating this data is presented The estimation is performedwith two single sensor and multi sensor approaches that use temporal and spatial correlation for estimation These methodshave been evaluated and compared with those that do not use the past of signal for estimation In addition flood detectionwithout probability of missing data is also compared with flood detection with probability of missing data based on estimateddata A laboratory system has been implemented for flood detection which is a wireless sensor network with the Zigbeeprotocol and star topology The implemented system consist of five nodes located where we intend to monitor there andsend level and flow of water data to a central node with a specified data structure These five nodes included level andflow of water sensors battery Arduino and transceiver module The central node receives the data and transfers it to thecomputer This data is stored on the computer in Excel and displayed visually with the Processing software The data isalso transmitted to Simulink and flood detection is performed on there Sleep mode of Arduino and transceiver module areused to optimize power consumption Key Words Wireless sensor network Compressive sensing Matrix completion Misseddata estimation Flood detection

جعفر قيصري

احسان يزديان

ايمان ايزدي، فريد شيخ‌الاسلام