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Development of an embedded system for human detection based-on thermal sensing and infrared imaging for nonurban environment application

Development of an embedded system for human detection based-on thermal sensing and infrared imaging for nonurban environment application / Tan Ting Feng
Dalam kajian ini, satu kaedah mengesan manusia dengan menggunakan pengesanan haba telah dicadangkan untuk menyelesaikan masalah pemburuan haram. Kawasan luar bandar telah dipilih sebagai tempat menguji fungsi sistem pengesanan manusia. Ciri-ciri manusia seperti keluasan permukaan dan orientasi akan diukur dan diguna dalam pembangunan sensor haba dan algoritma pemprosesan imej. Algoritma ini akan dimuat turun ke dalam Raspberry Pi 2 (RPi 2) dengan menggunakan reka bentuk berasaskan model dengan MATLAB dan Simulink. D6T MEMS sensor haba digunakan untuk mengesan sebarang kewujudan haba sebelum NoIR kamera berfungsi untuk menangkap beberapa imej. Imej-imej yang ditangkap akan diproses mengikut algoritma pengesanan manusia dan kewujudan manusia akan disahkan dengan menggunakan kaedah klasifikasi Support Vector Machine (SVM). Keputusan daripada eksperimen menunjukkan bahawa sistem ini dapat mengesan kehadiran manusia dengan ketepatan 100% bagi jarak daripada 3m sehingga 7m. Selain itu, penggunaan kuasa sistem pengesanan manusia telah diukur dan menunjukkan penjimatan tenaga sebanyak 10%. _______________________________________________________________________________________________________ In this study, a human detection with thermal sensing features is proposed to curb the poaching problem. Non-urban area is used as a testing site to prove the functionality of the module. The characteristics such as area and orientation of a human are measured and these are used in the development of the thermal sensing and image processing algorithm. The algorithm was implemented on a Raspberry Pi 2 (RPi 2) using Model-Based Design with MATLAB and Simulink. A D6T MEMS Thermal Sensor is used to detect any heat presence before a NoIR (No Infrared) camera module is used to capture multiple images. The images will be processed using a human detection algorithm and the presence of human will be verified using Support Vector Machine (SVM) classification method. The experimental results showed 100% of positive human detection for distance ranging from 3 to 7m. Furthermore, the power consumption of the human detection system is measured and shown to save energy by 10%.
Contributor(s):
Tan Ting Feng - Author
Primary Item Type:
Final Year Project
Identifiers:
Accession Number : 875006310
Language:
English
Subject Keywords:
human detection; thermal sensing; poaching problem
First presented to the public:
6/1/2016
Original Publication Date:
6/6/2018
Previously Published By:
Universiti Sains Malaysia
Place Of Publication:
School of Electrical & Electronic Engineering
Citation:
Extents:
Number of Pages - 107
License Grantor / Date Granted:
  / ( View License )
Date Deposited
2018-06-06 16:05:13.558
Date Last Updated
2019-01-07 11:24:32.9118
Submitter:
Mohd Jasnizam Mohd Salleh

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