scholarly journals Implementasi Video Streaming Lalu Lintas Kendaraan Dengan Server Raspberry Pi Menggunakan Protokol H.264

2018 ◽  
Vol 5 (5) ◽  
pp. 629
Author(s):  
Erfan Rohadi ◽  
Anastasia Merry Christine ◽  
Arief Prasetyo ◽  
Rosa Andrie Asmara ◽  
Indrazno Siradjuddin ◽  
...  

<p><strong>Abstrak</strong></p><p><strong><br /></strong>Teknologi <em>video surveillance system </em>atau kamera pengawas sudah menjadi alat yang sangat penting karena mayoritas kebutuhan masyarakat sekarang ini menginginkan informasi yang cepat untuk diakses serta praktis dalam penggunaannya. Dalam penelitian ini sebuah protokol H.264 dipergunakan dalam <em>memproses video streaming</em>pada <em>video surveillance system</em>yang berfungsi sebagai pengirim dan pengontrol paket data <em>streaming</em>dari kamera pengawas ke penerima yaitu sebagai <em>user video surveillance system</em>. Analisis <em>frame video</em>pada protokol H.264 dilakukan pada live streaming server berupa embedded system yang terintegrasi pada video <em>surveillance system</em>dengan kamera pengawas. Dari hasil uji coba menunjukan bahwa Protokol H.264 memberikan kompresi kualitas <em>video</em>yang baik, sehingga implementasi <em>Video Streaming</em>lalu lintas kendaraan ini menjanjikan dapat membantu memudahkan masyarakat dalam mendapatkan informasi dan juga mengetahui kondisi lalu lintas secara<em>realtime </em>serta efektif dan efesien. Implementasi <em>Video streaming</em>secara <em>realtime</em>ini memantau kondisi lalu lintas di suatu Lokasi dengan pendeteksi ketersediaan kamera CCTV <em>(Closed Circuit Television)</em>dan <em>Raspberry pi</em>sebagai <em>server</em>. </p><p> </p><p><em><strong>Abstract</strong></em></p><p><em><strong></strong></em><em><span>Technology of video surveillance system has become a very important tool because the majority of the needs of today's society want information that is fast to access and practical in its use. In this study an H.264 protocol is used in processing video streaming in video surveillance system that functions as a sender and controller of streaming data packets from surveillance camera to receiver that is as user video surveillance system. The frame video analysis of the H.264 protocol has performed on a live streaming server in the form of embedded systems integrated in video surveillance system with surveillance cameras As a result, the system shows that the H.264 protocol provides good video quality compression, so the implementation of Video Streaming traffic this vehicle promises to help facilitate the public in getting information and also know the real time traffic conditions as well as effective and efficient. Implementation streaming video in real time this monitor traffic conditions in a location with the detection of the availability of CCTV (Closed Circuit Television) and Raspberry Pi cameras as a server.</span></em></p>

Author(s):  
Adlan Hakim Ahmad ◽  
Sharifah Saon ◽  
Abd Kadir Mahamad ◽  
Cahyo Darujati ◽  
Sri Wiwoho Mudjanarko ◽  
...  

<div>This project investigates the use of face recognition for a surveillance system. The normal video surveillance system uses in closed-circuit television (CCTV) to record video for security purpose. It is used to identify the identity of a person through their appearances on the recorded video, manually. Today’s video surveillance camera system usually not occupied with a face recognition system. With some modification, a surveillance camera system can be used as face detection and recognition that can be done in real-time. The proposed system makes use of surveillance camera system that can identify the identity of a person automatically by using face recognition of Haar cascade classifier. The hardware used for this project were Raspberry Pi as a processor and Pi Camera as a camera module. The development of this project consist of three main phases which were data gathering, training recognizer, and face recognition process. All three phases have been executed using Python programming and OpenCV library, which have been performed in a Raspbian operation system. From the result, the proposed system successfully displays the output result of human face recognition, with facial angle within ±40°, in medium and normal light condition, and within a distance of 0.4 to 1.2 meter. Targeted image are allowed to wear face accessory as long as not covering the face structure. In conclusion, this system considered, can reduce the cost of manpower in order to identify the identity of a person in real time situation.</div>


2015 ◽  
Vol 42 (21) ◽  
pp. 7991-8005 ◽  
Author(s):  
Roberto Arroyo ◽  
J. Javier Yebes ◽  
Luis M. Bergasa ◽  
Iván G. Daza ◽  
Javier Almazán

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