Auto Pan Tilt Motion Surveillance System

2012 ◽  
Author(s):  
Pei Song Chee ◽  
Pei Ling Leow ◽  
Mohomad Shukri Abdul Manaf
Keyword(s):  
Motion Detection ◽  
Surveillance System ◽  
Low Cost ◽  
Outdoor Environment ◽  
Automated System ◽  
Maximum Speed ◽  
Camera System ◽  
Smart Surveillance ◽  
Blob Tracking ◽  
Smart Surveillance System

Projek ini bertujuan untuk membangunkan satu sistem yang dilengkapi dengan pelbagai jenis jejakkan. Sistem tersebut kecil dari segi saiz, mudah alih dan memudahkan pemasangan. Konvensyen sistem terdiri daripada fungsi operasi tunggal dan mempunyai sistem yang besar. Projek ini boleh dicapai dengan pemasangan webcam murah dengan dua motor servo yang memainkan peranan sebagai sendi gerakan. Gerakan tersebut berdasarkan proses menarik dan mendorong dengan sambungan yang terlekat pada motor. Sistem tersebut mampu melakukan tugas pengesanan objek, jejakkan warna dan jejakkan gumpalan warna cahaya laser. Selain itu, video rakaman, gambar tangkapan dan pencetusan penggera boleh dilakukan. Sistem pelbagai fungsi ini dibangunkan dengan algoritma gabungan dari pelbagai jenis penapis. Alat tersebut telah dicuba dalam keadaan bilik dan keadaan luaran. Kajian menunjukkan sistem mampu mengkompensasi dengan gangguan hingar. Sistem tersebut mampu mencapai kelajuan 0.125 ms–1 dengan 145° dan 60° periuk gerakan miring. Pemasangan system tersebut melibatkan kos yang murah dan boleh diaplikasikan dalam robot visi, persidangan video dan aplikasi UAV automatik. Kata kunci: Pengesanan gerakan; pelacakan gumpalan warna; pelacakan laser; sistem pemantauan pintar; kamera pelacakan objek This research develops webcam base pan and tilt camera with multiple tracking ability. This pan tilt surveillance system is small in size, portable and easy for installation. Convention surveillance system is limited to single function operation and have bulky camera system. The key component of this surveillance system is the attachment of low cost webcam onto pan and tilt servo motor. The movement of the webcam results from pulls and push coupling unit which attach to the motor. The smart surveillance system able to perform motion detection task, color blob tracking and laser light tracking. Automatic system enhanced its ability into real–time auto motion video record, photo snap shot and trigger alarm. This multi function system is developed with improve algorithm combination from different type of multi–filter. It is experimented under indoor and outdoor environment. The result shows the system able to compensate with the noise disturbance. The reported maximum speed is 0.125 ms–1 with 145° pan movement and 60° tilt movements. Such automated system is cost effective and can be used as robot vision, automated video conference and UAV application. Key words: Motion detection; color blob tracking; laser tracking; smart surveillance system; object tracking camera

scholarly journals Weapon Detection Using YOLO V3 for Smart Surveillance System

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Sanam Narejo ◽  
Bishwajeet Pandey ◽  
Doris Esenarro vargas ◽  
Ciro Rodriguez ◽  
M. Rizwan Anjum
Keyword(s):  
Object Detection ◽  
Transfer Learning ◽  
Surveillance System ◽  
Human Life ◽  
Automated System ◽  
Detection Model ◽  
Smart Surveillance ◽  
Computer Based ◽  
Smart Surveillance System ◽  
Detection And Recognition

Every year, a large amount of population reconciles gun-related violence all over the world. In this work, we develop a computer-based fully automated system to identify basic armaments, particularly handguns and rifles. Recent work in the field of deep learning and transfer learning has demonstrated significant progress in the areas of object detection and recognition. We have implemented YOLO V3 “You Only Look Once” object detection model by training it on our customized dataset. The training results confirm that YOLO V3 outperforms YOLO V2 and traditional convolutional neural network (CNN). Additionally, intensive GPUs or high computation resources were not required in our approach as we used transfer learning for training our model. Applying this model in our surveillance system, we can attempt to save human life and accomplish reduction in the rate of manslaughter or mass killing. Additionally, our proposed system can also be implemented in high-end surveillance and security robots to detect a weapon or unsafe assets to avoid any kind of assault or risk to human life.

scholarly journals Low-Cost Camera-Based Smart Surveillance System for Detecting, Recognizing, and Tracking Masked Human Face

2021 ◽  
Vol 15 (23) ◽  
pp. 104-119
Author(s):  
Ervan Adiwijaya Haryadi ◽  
Grafika Jati ◽  
Ario Yudo Husodo ◽  
Wisnu Jatmiko
Keyword(s):  
Surveillance System ◽  
Low Cost ◽  
Face Mask ◽  
Raspberry Pi ◽  
Surveillance Systems ◽  
Single Shot ◽  
Surveillance Camera ◽  
Smart Surveillance ◽  
The Face ◽  
Smart Surveillance System

A surveillance system is still the most exciting and practical security system to prevent crime effectively. The primary purpose of this system is to recognize the identity of the face caught by the camera. With the advancement of the Internet of things, surveillance systems were implemented on edge devices such as the low-cost Raspberry mobile camera. It raises the challenge of unstructured image/video where the video contains low quality, blur, and variations of human poses. The challenge is increasing because people used to wear a mask during the Covid -19 pandemic.  Therefore, we proposed developing an all-in-one surveillance system with face detection, recognition, and face tracking capabilities. This system integrated three modules: MTCNN face detector, VGGFace2 face recognition, and Discriminative Single-Shot Segmentation (D3S) tracker to create a system capable of tracking the faces of people caught on surveillance camera. We also train new face mask data to recognize and track. This system obtains data from the Raspberry Pi camera and processes images on the cloud as a mobile sensor approach. The proposed system successfully implemented and obtained competitive results in detection, recognition, and tracking under an unconstrained surveillance camera.

scholarly journals Remote Fault-Tolerant Control for Industrial Smart Surveillance System

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Atif Mahmood ◽  
Abdul Qayyum Khan ◽  
Ghulam Mustafa ◽  
Nasim Ullah ◽  
Muhammad Abid ◽  
...  
Keyword(s):  
Surveillance System ◽  
Fault Tolerant ◽  
Sufficient Conditions ◽  
Fault Tolerant Control ◽  
Linear Matrix ◽  
Control Law ◽  
Uncertain Network ◽  
Smart Surveillance ◽  
Communication Links ◽  
Smart Surveillance System

We design a remote fault-tolerant control for an industrial surveillance system. The designed controller simultaneously tolerates the effects of local faults of a node, the propagated undesired effects of neighboring connected nodes, and the effects of network-induced uncertainties from a remote location. The uncertain network-induced time delays of communication links from the sensor to the controller and from the controller to the actuator are modeled using two separate Markov chains and packet dropouts using the Bernoulli process. Based on linear matrix inequalities, we derive sufficient conditions for output feedback-based control law, such that the controller does not directly depend on output, for stochastic stability of the system. The simulation study shows the effectiveness of the proposed approach.

scholarly journals IoT Based Smart Surveillance System for Healthcare Monitoring using Raspberry PI

2019 ◽  
Vol 8 (12) ◽  
pp. 627-629
Keyword(s):  
Blood Pressure ◽  
Surveillance System ◽  
Heart Diseases ◽  
Electrical Signal ◽  
Raspberry Pi ◽  
Electronic Board ◽  
Pulse Sensor ◽  
Smart Surveillance ◽  
Healthcare Monitoring ◽  
Smart Surveillance System

IOT could be a trending in technology that can transform any device into a wise one a lot of industries setting out to utilize these technologies to extend their capacity and improve potency. These system has been created to detect people who are suffering with heart diseases, this framework is powered by Raspberry pi electronic board, which is worked on power control supply, Remote web availability by utilizing USB modem, it incorporates with sensors. pulse sensor which detects each beats per minute price. Temperature sensor detects the temperature variation, blood pressure sensor reads blood pressure and heart rate, ECG sensor which measures the electrical signal of the heart. it is an analog from converted in digital by using of SPI protocol. If any emergency occurs, it will raise a caution send it to the website and mobile though NOOBS Software. If any sensor parameter value more than the instructed value it will raise a beep sound

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