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Journal articles on the topic 'Intelligent surveillance system'

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Author: Grafiati

Published: 10 March 2023

Last updated: 11 March 2023

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1

Praveen, Dabbara. "Intelligent Video Surveillance System." International Journal for Research in Applied Science and Engineering Technology 9, no. VIII (August 15, 2021): 741–43. http://dx.doi.org/10.22214/ijraset.2021.37399.

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Intelligent video recognition with in-depth learning concept will create a self-paced video analytics program. CCTV cameras are used in all areas where safety is paramount. Manual monitoring seems tedious and time-consuming. Security can be defined by different words in different contexts such as identity theft, violence, explosions etc. Security monitoring is a tedious and time-consuming task. In this project we will analyse video feeds in real time and identify any unusual items such as violence or theft. The concept of in-depth learning simulates the functioning of the human brain in processing data for use in acquisition, speech recognition, decision making, etc. This will depend without human guidance, from unstructured and unlabelled data.

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2

Sanoob, A. H., J. Roselin, and P. Latha. "Smartphone Enabled Intelligent Surveillance System." IEEE Sensors Journal 16, no. 5 (March 2016): 1361–67. http://dx.doi.org/10.1109/jsen.2015.2501407.

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3

Liu, Hong Tao. "Design of Low-Cost Airport Boundary Intelligent Video Surveillance System." Applied Mechanics and Materials 443 (October 2013): 228–32. http://dx.doi.org/10.4028/www.scientific.net/amm.443.228.

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The existing Airport boundary intelligent video surveillance system is complicated to construct and costs a lot. This paper presents a design of economical Airport boundary intelligent video surveillance system according to the principle of optimization system and the resources share, combined the motion detection technology of NVR with intelligence video analyze equipment. The design can greatly decrease the false alarm rate and reduced the number of intelligence video analysis equipment. Therefor, it has higher application value and practical significance.

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4

Rghioui, Amine, Jaime Lloret, Mohamed Harane, and Abdelmajid Oumnad. "A Smart Glucose Monitoring System for Diabetic Patient." Electronics 9, no. 4 (April 22, 2020): 678. http://dx.doi.org/10.3390/electronics9040678.

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Diabetic patients need ongoing surveillance, but this involves high costs for the government and family. The combined use of information and communication technologies (ICTs), artificial intelligence and smart devices can reduce these costs, helping the diabetic patient. This paper presents an intelligent architecture for the surveillance of diabetic disease that will allow physicians to remotely monitor the health of their patients through sensors integrated into smartphones and smart portable devices. The proposed architecture includes an intelligent algorithm developed to intelligently detect whether a parameter has exceeded a threshold, which may or may not involve urgency. To verify the proper functioning of this system, we developed a small portable device capable of measuring the level of glucose in the blood for diabetics and body temperature. We designed a secure mechanism to establish a wireless connection with the smartphone.

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5

Maldonado, Kenly, and Steve Simske. "Situational Strategic Awareness Monitoring Surveillance System–Microcomputer and Microcomputer Clustering used for Intelligent, Economical, Scalable, and Deployable Approach for Safeguarding Materials." Electronic Imaging 2020, no. 3 (January 26, 2020): 60408–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.3.mobmu-336.

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The principal objective of this research is to create a system that is quickly deployable, scalable, adaptable, and intelligent and provides cost-effective surveillance, both locally and globally. The intelligent surveillance system should be capable of rapid implementation to track (monitor) sensitive materials, i.e., radioactive or weapons stockpiles and person(s) within rooms, buildings, and/or areas in order to predict potential incidents proactively (versus reactively) through intelligence, locally and globally. The system will incorporate a combination of electronic systems that include commercial and modifiable off-the-shelf microcomputers to create a microcomputer cluster which acts as a mini supercomputer which leverages real-time data feed if a potential threat is present. Through programming, software, and intelligence (artificial intelligence, machine learning, and neural networks), the system should be capable of monitoring, tracking, and warning (communicating) the system observer operations (command and control) within a few minutes when sensitive materials are at potential risk for loss. The potential customer is government agencies looking to control sensitive materials and/or items in developing world markets intelligently, economically, and quickly.

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Maldonado, Kenly, and Steve Simske. "Situational Strategic Awareness Monitoring Surveillance System—Microcomputer and Microcomputer Clustering used for Intelligent, Economical, Scalable, and Deployable Approach for Safeguarding Materials." Journal of Imaging Science and Technology 63, no. 6 (November 1, 2019): 60408–1. http://dx.doi.org/10.2352/j.imagingsci.technol.2019.63.6.060408.

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Abstract The principal objective of this research is to create a system that is quickly deployable, scalable, adaptable, and intelligent and provides cost-effective surveillance, both locally and globally. The intelligent surveillance system should be capable of rapid implementation to track (monitor) sensitive materials, i.e., radioactive or weapons stockpiles and person(s) within rooms, buildings, and/or areas in order to predict potential incidents proactively (versus reactively) through intelligence, locally and globally. The system will incorporate a combination of electronic systems that include commercial and modifiable off-the-shelf microcomputers to create a microcomputer cluster which acts as a mini supercomputer which leverages real-time data feed if a potential threat is present. Through programming, software, and intelligence (artificial intelligence, machine learning, and neural networks), the system should be capable of monitoring, tracking, and warning (communicating) the system observer operations (command and control) within a few minutes when sensitive materials are at potential risk for loss. The potential customer is government agencies looking to control sensitive materials and/or items in developing world markets intelligently, economically, and quickly.

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7

Rothkrantz, Leon, Madalina Toma, and Mirela Popa. "AN INTELLIGENT CO-DRIVER SURVEILLANCE SYSTEM." Acta Polytechnica CTU Proceedings 12 (December 15, 2017): 83. http://dx.doi.org/10.14311/app.2017.12.0083.

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In recent years many car manufacturers developed digital co-drivers , which are able to monitor the driving behaviour of a car. Sensors in the car measure if a car passes speed limits, leaves its lane, or violates other traffic rules. A new generation of co-drivers is based on sensors in the car which are able to monitor the driver behaviour. Driving a car is a sequence of actions. In case a driver doesn’t show one of the actions the co-driver generates a warning signal. Experiments in the car simulator TORC were performed to extract the actions of a car driver. These actions were used to develop probabilistic models of the driving behaviour. A prototype of a warning system has been developed and tested in the car simulator. The experiments and test results will be reported in this paper.

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8

Sasikala, G., and R. S. Lekha. "Intelligent Surveillance System for Smart Security." Indian Journal of Science and Technology 12, no. 29 (August 1, 2019): 1–9. http://dx.doi.org/10.17485/ijst/2019/v12i29/147083.

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9

Nam, Yunyoung, Seungmin Rho, and Jong Hyuk Park. "Intelligent video surveillance system: 3-tier context-aware surveillance system with metadata." Multimedia Tools and Applications 57, no. 2 (December 22, 2010): 315–34. http://dx.doi.org/10.1007/s11042-010-0677-x.

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10

Mahibha, Akshaya S. Yamini E. Veeshal Sheev V. B. C. Jerin. "An Intelligent Fire Detection and Surveillance System." International Journal of Computer Sciences and Engineering 06, no. 03 (April 30, 2018): 158–62. http://dx.doi.org/10.26438/ijcse/v6si3.158162.

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11

Jeon, Hyoung-Seok, Dong-Hae Yeom, and Young-Hoon Joo. "Video-based Intelligent Unmanned Fire Surveillance System." Journal of Korean Institute of Intelligent Systems 20, no. 4 (August 25, 2010): 516–21. http://dx.doi.org/10.5391/jkiis.2010.20.4.516.

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12

Tsai, Tsung-Han, and Shih-Wei Chen. "Single-Chip Design for Intelligent Surveillance System." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 26, no. 9 (September 2018): 1637–46. http://dx.doi.org/10.1109/tvlsi.2018.2827385.

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13

Yazdanbakhsh, Omolbanin, Yu Zhou, and Scott Dick. "An intelligent system for livestock disease surveillance." Information Sciences 378 (February 2017): 26–47. http://dx.doi.org/10.1016/j.ins.2016.10.026.

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14

Thanthry, Naagaraja, Indira Emmuadi, Aravind Srikumar, Kamesh Namuduri, and Ravi Pendse. "SVSS: Intelligent video surveillance system for aircraft." IEEE Aerospace and Electronic Systems Magazine 24, no. 10 (October 2009): 23–29. http://dx.doi.org/10.1109/maes.2009.5317783.

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15

Yoon, Tae-Ho, and Yoo-Seoung Song. "Emphasizing Intelligent Event Processing Cooperative Surveillance System." IEMEK Journal of Embedded Systems and Applications 7, no. 6 (December 31, 2012): 339–43. http://dx.doi.org/10.14372/iemek.2012.7.6.339.

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16

Wu, Shuo Mei, Jian Wei Song, and Xu Ning Liu. "Application Research of Intelligent Monitoring System Based on Abnormal Events." Applied Mechanics and Materials 713-715 (January 2015): 471–74. http://dx.doi.org/10.4028/www.scientific.net/amm.713-715.471.

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In order to meet the needs of the construction information industry base, enhance their ability to serve the community, and improve scientific research projects of market-oriented level, then develop family-oriented and school-based intelligent monitoring software system, the development of new products in the smart camera and mobile video surveillance and development of new technologies are developed. It is considered that the electronic information industry needs to develop intelligent monitoring technology industry, the video compression technology and the use of mobile and existing wireless networks are made, such as efforts are used to complete the smart cameras and mobile video surveillance system development, so the development of application research has implemented the front of video surveillance intelligence information collection, transmission of video signals in real time, real-time wireless video signal transmission and other tasks.

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17

Li, Yang, Qing Hong Wu, and Xue Xiao. "Based Embedded System Applications in Intelligent Home Remote Monitoring." Applied Mechanics and Materials 602-605 (August 2014): 2317–20. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.2317.

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With the continuous improvement of security awareness, home security has become the focus of attention. The actual demand for home video surveillance system, designed a cheap, practical, small size and low power consumption of video surveillance systems, this paper uses microprocessor S3C2440 ARM9 core as the core hardware control, embedded Linux operating system with software the control core, and cheap, generic USB camera video capture device as a front end to complete the design of a home video surveillance system.

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18

Nouby, M. "Intelligent Wireless Surveillance of Multirate Induction Motors." International Journal on Recent and Innovation Trends in Computing and Communication 8, no. 2 (February 29, 2020): 01–05. http://dx.doi.org/10.17762/ijritcc.v8i2.5421.

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Recent advances in the automation field provide a wide range of scope in control and monitoring of the industrial systems. A very accurate automation system is on high demand in recent times. This paper mainly deals about remote monitoring and control of the induction motor. The main objective is to develop an embedded system to prevent the occurrence of line fault in a three phase system (say induction motor) and to display and control the parameters voltage, speed and temperature of the three phase system using Zig-bee communication technology. An ARM microcontroller is used in this project, which controls the entire operation of the system, which also communicates various parameters from one part of the system to other through Zig-bee technology. To prevent the issues of poor blunder elements and commotion affectability emerging in functional applications, the plan issue is changed into a proportional Linear Matrix Inequality (LMI) structure to understand a vigorous state criticism roughly by quick yield testing .The control objective is encircled with rise time, overshoot and settling time particulars. Subsequent to arriving at the consistent express the controller ought to look after solidness. To fulfill the above prerequisites a quick yield inspecting control calculation is planned with the end goal that the ideal shut circle conduct and shut circle soundness is accomplished. The exhibition of the framework is broke down for controlling the speed through wireless networks.

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19

He, Fangcheng. "Intelligent Video Surveillance Technology in Intelligent Transportation." Journal of Advanced Transportation 2020 (November 12, 2020): 1–10. http://dx.doi.org/10.1155/2020/8891449.

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Along with the strength of the country’s overall strength, the people’s pockets have become more and more popular, and there have been significant improvements in all aspects of life, especially in terms of travel methods. This reflects the increase in residents’ income, but it also brings huge traffic pressure. In the long run, traffic congestion is not only detrimental to urban development, but frequent traffic accidents threaten residents’ travel safety. Effective monitoring methods are essential to solving these problems, so it is necessary to carry out research on intelligent video monitoring technology in intelligent transportation. The purpose of this article is to solve the current situation of excessive traffic pressure in the city. Through the study of intelligent video surveillance technology in intelligent traffic, the use of constrained least squares algorithm to remove motion blur and apply Kalan filtering to the sharpening process is used to eliminate noise ambiguity and make a brief introduction to various classic moving target detection methods to realize real-time monitoring of intelligent traffic conditions and continuously adjust and verify the monitoring situation, and then establish intelligent video in intelligent traffic monitoring technology research system. The research results show that this kind of intelligent video surveillance technology research in intelligent transportation can effectively increase the awareness of intelligent video surveillance technology and improve the level of intelligent video surveillance technology. The data measurement time has been shortened by one hour, the aggregation time has been changed from three hours to two hours, and the analysis time has been shortened by half. Eased urban traffic road pressure and greatly reduced the incidence of traffic accidents, which is conducive to socialist harmony social construction.

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20

Zhang, Yu Xin, Fu Quan Li, Xi Tao, and Guo Yu Lin. "Design and Implementation of an Intelligent Video Surveillance System Based on Android Phone." Advanced Materials Research 816-817 (September 2013): 1126–30. http://dx.doi.org/10.4028/www.scientific.net/amr.816-817.1126.

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This paper proposes a new intelligent video surveillance system based on Android phone. By using Android phone, this system can be deployed easily and quickly. Compare with the traditional surveillance system, this new one uses Android phone to replace the large and expensive surveillance cameras. In addition, the functions of back-end equipment of the traditional system have been moved to the front-end equipment. With a modified invasion detection algorithm, the front-end equipment becomes more intelligent. This schema can significantly increase the mobility and flexibility of the entire system. Therefore this system will have a better performance dealing with emergencies in different surveillance scenarios. Moreover, this state-of-art intelligent video surveillance system not only brings a new method for surveillance, but also advances the development of surveillance techniques.

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21

Yang, Gang, Xin Tan, and Yong Rui Zhang. "An Intelligent Video Surveillance System for Android Smart Phone." Advanced Materials Research 850-851 (December 2013): 884–88. http://dx.doi.org/10.4028/www.scientific.net/amr.850-851.884.

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Video surveillance technology is playing an important role, and it is widely used in some fields. With the popularity of Android OS, it draws researchers attention to increase the development of video surveillance systems on the platform. This paper presents a smart real-time video surveillance system based on Android smart phone. This system detects moving object by using improved GMM (Gaussian Mixture Mode) algorithm, recognizes invading human with cascade classifier, processes image data with coder & decoder, transmits data over RTP (Real-time Transport Protocol). It also applies some methods to improve the accuracy of moving object detection and recognition, speed up recognition process. The experimental evidences show that it can realize real-time video surveillance and smart alarm.

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Xu, Feng. "Applied-Information Technology in Abnormal Detection for Surveillance Systems." Advanced Materials Research 1046 (October 2014): 266–69. http://dx.doi.org/10.4028/www.scientific.net/amr.1046.266.

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In recent years, video surveillance has become more and more important for enhanced security and it is indispensable technology for fighting against all types of crime with the construction of sky-net in China. Abnormal detection is the focus of intelligent video surveillance and the information of abnormal behavior can be used in the investigation of criminal cases, which combines computer vision and artificial intelligence technology and has wide application prospect in public security work. In this paper, first the current research situation of the intelligent surveillance system is introduced. Then the category of abnormal behavior detection is expounded. Finally the function module of abnormal detection system is designed and the key technology of moving target detection, target tracking and abnormality judgment is discussed in view of the actual situation of surveillance system in criminal cases.

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23

Zhu, Mingjiang. "Application of Moving Target Information Perception Technology in Intelligent Supervision System." Scanning 2022 (August 31, 2022): 1–7. http://dx.doi.org/10.1155/2022/5192601.

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In order to solve the problems of inaccurate information collection, incomplete information collection, and inconsistency of collected images in traditional sports injury collection methods, an application method of moving target information perception technology in intelligent supervision system is proposed. By judging and analyzing the potential motion damage posture of the motion posture intelligent tracking images, the collected motion intelligence tracking images are judged. The intelligent tracking image matrix can make up for the shortcomings of traditional images that are not connected, complete the identification, detect potential damage in time, and take targeted preventive measures and means. Finally, according to the target detection algorithm and target tracking algorithm, combined with OpenCV computer vision library and QT image library, an intelligent video surveillance target tracking simulation system is developed. The algorithm studied in this paper is to realize the target tracking function of the intelligent video surveillance system. Through the comparison of experimental results, the design method can accurately collect damage attitude information, without calculating continuous values, and the use of three-dimensional images in the positioning process can analyze the damage attitude from multiple angles.

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Liu, Yu, and Chao Zhang. "The Auxiliary System of Video Surveillance in Smart Substation." Journal of Physics: Conference Series 2195, no. 1 (February 1, 2022): 012030. http://dx.doi.org/10.1088/1742-6596/2195/1/012030.

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Abstract With the continuous development of artificial intelligence technology, the current substation operation and maintenance personnel have more and more urgent needs for the visualization, remoteness and intelligence of the operation and maintenance system. In order to solve the existing problems and present situation, key technologies such as image acquisition, image recognition, and visual display are studied. A smart substation video monitoring auxiliary system was developed. The system is used advanced cameras and acquisition equipment to monitor and detect related electrical equipment such as hard pressure plate switches in the substation in real time. The goal of intelligent inspection is achieved. In the smart substation project, it has achieved good results and has a wide range of application prospects.

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Sabri, Zaid Saeb, and Zhiyong Li. "Low-cost intelligent surveillance system based on fast CNN." PeerJ Computer Science 7 (February 25, 2021): e402. http://dx.doi.org/10.7717/peerj-cs.402.

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Smart surveillance systems are used to monitor specific areas, such as homes, buildings, and borders, and these systems can effectively detect any threats. In this work, we investigate the design of low-cost multiunit surveillance systems that can control numerous surveillance cameras to track multiple objects (i.e., people, cars, and guns) and promptly detect human activity in real time using low computational systems, such as compact or single board computers. Deep learning techniques are employed to detect certain objects to surveil homes/buildings and recognize suspicious and vital events to ensure that the system can alarm officers of relevant events, such as stranger intrusions, the presence of guns, suspicious movements, and identified fugitives. The proposed model is tested on two computational systems, specifically, a single board computer (Raspberry Pi) with the Raspbian OS and a compact computer (Intel NUC) with the Windows OS. In both systems, we employ components, such as a camera to stream real-time video and an ultrasonic sensor to alarm personnel of threats when movement is detected in restricted areas or near walls. The system program is coded in Python, and a convolutional neural network (CNN) is used to perform recognition. The program is optimized by using a foreground object detection algorithm to improve recognition in terms of both accuracy and speed. The saliency algorithm is used to slice certain required objects from scenes, such as humans, cars, and airplanes. In this regard, two saliency algorithms, based on local and global patch saliency detection are considered. We develop a system that combines two saliency approaches and recognizes the features extracted using these saliency techniques with a conventional neural network. The field results demonstrate a significant improvement in detection, ranging between 34% and 99.9% for different situations. The low percentage is related to the presence of unclear objects or activities that are different from those involving humans. However, even in the case of low accuracy, recognition and threat identification are performed with an accuracy of 100% in approximately 0.7 s, even when using computer systems with relatively weak hardware specifications, such as a single board computer (Raspberry Pi). These results prove that the proposed system can be practically used to design a low-cost and intelligent security and tracking system.

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Jang, Jae-Hyuk, and Gab-Sig Sim. "Intelligent Mobile Surveillance System Based on Wireless Communication." Journal of the Korea Contents Association 15, no. 2 (February 28, 2015): 11–20. http://dx.doi.org/10.5392/jkca.2015.15.02.011.

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DENGYun and CHENG Xiaohui. "Research and Design of Intelligent Video Surveillance System." International Journal of Advancements in Computing Technology 4, no. 11 (June 30, 2012): 378–88. http://dx.doi.org/10.4156/ijact.vol4.issue11.41.

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Ulyev, A. D., V. L. Rozaliev, A. V. Zaboleeva-Zotova, and Y. A. Orlova. "An Intelligent Video Surveillance System for Human Behavior." Scientific and Technical Information Processing 48, no. 5 (December 2021): 388–97. http://dx.doi.org/10.3103/s0147688221050117.

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Li, Liwei, Haibin Xie, and Peng Li. "Intelligent Video Surveillance System Based on Cloud Network." Journal of Physics: Conference Series 2025, no. 1 (September 1, 2021): 012021. http://dx.doi.org/10.1088/1742-6596/2025/1/012021.

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Abstract There are two shortcomings in traditional video surveillance systems: First, the amount of data is so huge that the processing, analysis, and viewing of massive data requires a lot of manpower, material resources and financial resources. Second, it is difficult to store and transmit video data. Mass video data often needs to be stored and passed to the backstage for analysis, and huge data makes data storage and transmission difficult. In view of the above trouble, this paper proposes a set of intelligent video surveillance system based on cloud network. It contains modules such as face detection, quick retrieval, etc., and uses the cloud network as a medium to transmit data and information. It can complete the automatic detection, capture, enhancement, and coding processing of the human face in the video, search and compare with the background database automatically and quickly.

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Tang, Zhi Wei, and Xi Xuan Wu. "One Intelligent Video Surveillance System Based on DM642." Key Engineering Materials 474-476 (April 2011): 392–97. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.392.

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This article introduces an intelligent surveillance distributed system based on TMS320DM642. The system platform has many functions, such as OSD (on screen display), analog video output, digital video output, Hard Disk, Ethernet and so on. DM64. User can set the rules via the management software. The video input from analog cameras and IP cameras can be processed by DM642 according to the rules. If any event happens which acts against the rules, alarm will be given. The system provides immediate, accurate and intelligent services for users. In order to realize the complex image processing algorithms on DM642, we optimize the algorithms based on DSP and propose a series of rapid image processing algorithms. The design of the project puts the emphasis on the feasibility of distributed high-performance processing from both hardware and software aspects, which may be easily applied to other large scale or hard real-time intelligent information processing.

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Zhao, Ying, Tian Fei Zhou, and Shao Qian Wei. "Crowd Abnormal Behavior Recognition in Intelligent Surveillance System." Applied Mechanics and Materials 263-266 (December 2012): 2592–96. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.2592.

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Crowd abnormal behavior recognition is essential for intelligent visual surveillance in public places to ensure the safety of the public. This is a challenging work because crowd behaviors are complex which are influenced by various factors. This paper divided these factors into three categories: physical factors, social factors and psychological factors. Then an overview about crowd behavior modeling approaches was given. After that, the paper described and analyzed some influential existing algorithms in crowd abnormal behavior recognition from the view point of behavioral factors they used. Finally, the paper discussed the future research directions in this area and some research proposals were given.

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Jia, Peng, and Shujuan Yang. "China needs a national intelligent syndromic surveillance system." Nature Medicine 26, no. 7 (May 20, 2020): 990. http://dx.doi.org/10.1038/s41591-020-0921-5.

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Park, Ho-Sik. "Active Object Tracking System for Intelligent Video Surveillance." Journal of Korea Institute of Information, Electronics, and Communication Technology 7, no. 2 (June 30, 2014): 82–85. http://dx.doi.org/10.17661/jkiiect.2014.7.2.082.

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Kim, Do Hyun, Jung Eun Kim, Ji Hag Song, Yong Jun Shin, and Sung Soo Hwang. "Image-based Intelligent Surveillance System Using Unmanned Aircraft." Journal of Korea Multimedia Society 20, no. 3 (March 30, 2017): 437–45. http://dx.doi.org/10.9717/kmms.2017.20.3.437.

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Li, Hongguang, Xinhua Feng, Deming Wu, and Lifeng Liang. "Design of Intelligent Surveillance System for Cable Connector." IOP Conference Series: Earth and Environmental Science 598 (November 25, 2020): 012096. http://dx.doi.org/10.1088/1755-1315/598/1/012096.

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Sun, Zhidong, Jie Sun, and Xueqing Li. "Research on Video Quality Diagnosis Technology Based on Artificial Intelligence and Internet of Things." Wireless Communications and Mobile Computing 2021 (December 29, 2021): 1–6. http://dx.doi.org/10.1155/2021/2460916.

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The remote video diagnosis system based on the Internet of Things is based on the Internet of Things and integrates advanced intelligent technology. To better promote a harmonious society, constructing a video surveillance system is accelerating in our country. Many enterprises and government agencies have invested much money to build video surveillance systems. The quality of video images is an important index to evaluate the video surveillance system. However, as the number of cameras continues to increase, the monitoring time continues to extend. In the face of many cameras, it is not realistic to rely on human eyes to diagnose video-solely quality. Besides, due to human eyes’ subjectivity, there will be some deviation in diagnosis through human eyes, and these factors bring new challenges to system maintenance. Therefore, relying on artificial intelligence technology and digital image processing technology, the intelligent diagnosis system of monitoring video quality is born using the computer’s efficient mathematical operation ability. Based on artificial intelligence, this paper focuses on studying video quality diagnosis technology and establishes a video quality diagnosis system for video definition detection and noise detection. This article takes the artificial intelligence algorithm in the diagnosis of video quality effect. Compared with the improved algorithm, the improved video quality diagnosis algorithm has excellent improvement and can well finish video quality inspection work. The accuracy of the improved definition evaluation function for the definition detection of surveillance video and noise detection is as high as 95.56%.

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Xi, Zhi Hong, and Guang Hui Dong. "Moving Objects Detection and Speed Estimation in Intelligent Surveillance System." Advanced Materials Research 712-715 (June 2013): 2354–58. http://dx.doi.org/10.4028/www.scientific.net/amr.712-715.2354.

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In order to solve the problem of highway intelligent video surveillance system for effective monitoring of vehicle operating conditions, a fast block background modeling method is proposed in the framework for intelligent video surveillance system. First using statistical histogram to build the background model of the video surveillance system, second using background subtraction method to locate the moving target area, at last using displacement of the minimum exterior rectangle centroid of the moving target between two frames to calculate moving target speed, without the aid calibration. Experimental results show that the proposed method exhibits its superiority in processing time, the time of building background model through 100 frames is 3.8s. The proposed method has good practical value used in intelligent video surveillance.

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Yang, Biao, Guo Yu Lin, and Wei Gong Zhang. "An Embedded System Used as Intelligent Node of Distributed Surveillance." Applied Mechanics and Materials 475-476 (December 2013): 763–66. http://dx.doi.org/10.4028/www.scientific.net/amm.475-476.763.

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The demand for intelligent surveillance is grown with the popularization of the camera monitoring network. An embedded system used as intelligent node of distributed surveillance is designed in this paper to improve the intelligent level of camera monitoring. Target detection and tracking can be implemented in this node and an anomaly intrusion detection system is designed based on the tracking results. Information sharing is realized via transmitting highly abstract object descriptors via the wireless network. A simple camera monitoring network is built in the labs to test the designed intelligent node and the experimental results indicate its effectiveness and accuracy.

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Ivanov, Yurii, Borys Sharov, Nazar Zalevskyi, and Ostap Kernytskyi. "Software System for End-Products Accounting in Bakery Production Lines Based on Distributed Video Streams Analysis." Advances in Cyber-Physical Systems 7, no. 2 (December 16, 2022): 101–7. http://dx.doi.org/10.23939/acps2022.02.101.

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Among the main requirements of modern surveillance systems are stability in the face of negative influences and intellectualization. The purpose of intellectualization is that the surveillance system should perform not only the main functions such as monitoring and stream recording but also have to provide effective stream processing. The requirement for this processing is that the system operation has to be automated, and the operator's influence should be minimal. Modern intelligent surveillance systems require the development of grouping methods. The context of the grouping method here is associated with a decomposition of the target problem. Depending on the purpose of the system, the target problem can represent several subproblems, each of which usually accomplishes by artificial intelligence or data mining methods.

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Marois, Alexandre, Daniel Lafond, Alexandre Williot, François Vachon, and Sébastien Tremblay. "Real-Time Gaze-Aware Cognitive Support System for Security Surveillance." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (December 2020): 1145–49. http://dx.doi.org/10.1177/1071181320641274.

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Security surveillance entails many cognitive challenges (e.g., task interruption, vigilance decrements, cognitive overload). To help surveillance operators overcome these difficulties and perform more efficient visual search, gaze-based intelligent systems can be developed. The present study aimed at testing the impact of the Scantracker system—which pinpointed neglected cameras while detecting and correcting attentional tunneling and vigilance decrease—on human scanning behavior and surveillance performance. Participants took part in a surveillance simulation, monitoring cameras and searching for ongoing incidents, and half of them was supported by the Scantracker. Although behavioral surveillance performance was not improved, participants supported by the Scantracker showed more efficient gaze-based measures of surveillance. Moreover, some of these measures were associated with performance, suggesting that scan pattern improvements might lead indirectly to more efficient incident detection. Overall, these results speak to the potential of using gaze- aware intelligent systems to support surveillance operators.

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Przybylo, Jaromir. "Object detection and tracking for low-cost video surveillance system." Image Processing & Communications 18, no. 2-3 (December 1, 2013): 91–99. http://dx.doi.org/10.2478/v10248-012-0083-2.

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Abstract Automated and intelligent video surveillance systems play important role in the modern world. Since the amount of various video streams that must be analyzed grows, such artificial intelligence systems can assist humans in performing tiresome tasks. As a result, the effectiveness of response to a dangerous situations is increasing (detect unexpected movement or unusual behavior that may pose a threat to people, property and infrastructure). Video surveillance systems have to meet several requirements: must be accurate and not produce too many false alarms, moreover it must be able to process the received video stream in real-time to provide a sufficient response time. The work presented here focuses on the selected challenges of scene analysis in video surveillance systems (object detection/tracking, effectiveness of the whole system). The aim of the research is to design a low-budget surveillance system, that can be used for example in a home security monitoring. Such solution can be use not only to surveillance but also to monitor elderly person at home or provide new ways of interacting in human-computer interaction systems.

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Zhang, Kai. "Intelligent Video Analysis System Based on ARM Cortex." Applied Mechanics and Materials 556-562 (May 2014): 3216–18. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.3216.

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With the development of the society, security monitoring system more and more get people's attention. Article designs the intelligent video analysis technology based on ARM architecture on the basis of Intelligent Video Surveillance, and discusses the application prospect of intelligent video analysis system.

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She, Chuyun, Runlan Zheng, Qiaoyin Yang, and Shaowei Liang. "Research of Intelligent Video Surveillance System based on Artificial Neural Network." Journal of Physics: Conference Series 2181, no. 1 (January 1, 2022): 012057. http://dx.doi.org/10.1088/1742-6596/2181/1/012057.

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Abstract In order to improve the video monitoring capabilities, this paper designs an intelligent video surveillance system. Firstly, it analyzes the current problems of video surveillance, and then proposes intelligent requirement in three aspects. In the training process, the model is obtained by searching, gray conversion, and training. Finally, the correctness of this system is verified by the actual application in real station.

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Li, Chuanfeng, Yunxing Shu, and Mingming Zhao. "Design of Intelligent Surveillance System Based on Wireless Video Transmission and PID Multiplexed Control Strategy." Open Electrical & Electronic Engineering Journal 9, no. 1 (September 30, 2015): 467–73. http://dx.doi.org/10.2174/1874129001509010467.

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A kind of wireless video transmission intelligence surveillance system is developed to perform work normally done by human being in hazardous environment, narrow space, as well as chemical and toxic places. This system consists of two main parts: a host computer with monitoring software and a mobile intelligent vehicle. The host computer software can provide real-time display of video, temperature, humidity, light intensity and other environmental information collected by the intelligent vehicle, and can control the movement direction, movement speed of the intelligent vehicle as well as the camera platform angle with control buttons. The vehicle can collect images and sensor data, and transmit them to the host computer via wireless fidelity (WIFI). The speed of intelligent vehicle is regulated by joint control of position type proportion integration differentiation (PID) and bang-bang control strategy. The video is captured by universal serial bus (USB) interface camera, and transmitted to the host computer by WIFI for real-time display. The testing results show that the system can not only display clear video images, but also accurately display the dynamic data of sensors. At the same time, the host computer can reliably control the multi-directional movement, grabbing obstacles and changing camera platform angle of the intelligent vehicle.

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Lee, R. "iJADE surveillant—an intelligent multi-resolution composite neuro-oscillatory agent-based surveillance system." Pattern Recognition 36, no. 6 (June 2003): 1425–44. http://dx.doi.org/10.1016/s0031-3203(02)00255-8.

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Reddy, Y. Harshavardhan, Adnan Ali, A. Zaheer Sha, P. Madhulaya, P. Madhulatha, G. Varahi, P. Lakshmisravya, and R. Varaprasad. "Photovoltaic, Internet-of-Things-Enabled Intelligent Agricultural Surveillance System." South Asian Research Journal of Engineering and Technology 4, no. 5 (September 4, 2022): 78–85. http://dx.doi.org/10.36346/sarjet.2022.v04i05.001.

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The implementation of wireless communication technologies for monitoring and control systems resulted in the first instance of "smart" farming. Precision agriculture (PA) is characterized by the employment of cutting-edge technology and equipment calibrated to the inch to precisely monitor and treat crops. Smart PA is able to assist farmers in increasing crop yields and simultaneously increasing efficiency and reducing stress by utilising wireless sensor networks (WSNs) and the Internet of Things (IoT). In this paper, an Internet of Things–enabled agricultural monitoring system is discussed. Data on the environment will be gathered in the field by solar-powered prototype nodes, and then transmitted to a central station for processing. Utilizing two nodes, it was determined whether or not it is advantageous to add energy harvesting into an electrical device. An experimental testbed demonstrates how the system might work in the future by capturing energy. Using a gadget that can harvest energy can lengthen the amount of time a device is able to run by supplying it with electricity, charging the battery, and increasing the battery's capacity.

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Park, Jung-Hyun, Hong-Gi Yeom, Bong-Gyu Jung, In-Hun Jang, and Kwee-Bo Sim. "Soundsource Localization and Tracking System of Intruder for Intelligent Surveillance System." Journal of Korean Institute of Intelligent Systems 17, no. 6 (December 25, 2007): 786–91. http://dx.doi.org/10.5391/jkiis.2007.17.6.786.

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Carpenter, Chris. "Waterflood Optimization Advisory System Provides Insights Into Efficiency." Journal of Petroleum Technology 74, no. 11 (November 1, 2022): 70–72. http://dx.doi.org/10.2118/1122-0070-jpt.

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_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 207946, “Intelligent Waterflood Optimization Advisory System: A Step Change Toward Digital Transformation,” by Samat Ramatullayev, SPE, Muzahidin M. Salim, and Muhammad Ibrahim, SPE, Schlumberger, et al. The paper has not been peer reviewed. _ In the complete paper, the authors discuss the development of an end-to-end waterflooding-optimization system that provides monitoring and surveillance dashboards with artificial-intelligence (AI) and machine-learning (ML) components to generate and assess insights into operational efficiency in an automated manner. The system allows for fast screening of waterflooding performance at diverse levels, enabling prompt identification of opportunities for immediate uptake into an opportunity-management process and for evaluation in an AI-driven production forecast or a reservoir simulator. Monitoring and Surveillance Dashboards The system consists of a series of dashboards covering both subsurface and surface elements. The production data foundation, the data-management platform, can connect to multiple data sources, simplifying data-preparation and -ingestion processes. The intelligent monitoring and surveillance section consists of monitoring and surveillance dashboards focusing on six key indicators: production scorecard, injection scorecard, injection efficiency, voidage replacement ratio, injection-water quality, advanced analytics, and opportunity management. The system consists of different modules such as Field, Reservoir, Sector, Pattern, Offset Wells, Surface Facilities, and Advanced Analytics. Although each module contains some automation aspects, the Advanced Analytics module houses most of the automation and ML. The modules are detailed in the complete paper.

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Khodadin, Fatimah, and Sameerchand Pudaruth. "An Intelligent Camera Surveillance System with Effective Notification Features." International Journal of Computing and Digital Systems 09, no. 6 (November 1, 2020): 1251–61. http://dx.doi.org/10.12785/ijcds/0906022.

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Kapoor, Surbhi. "An Intelligent Video Surveillance System: Moving Object Behavior Analysis." Indian Journal of Science and Technology 9, no. 1 (January 20, 2016): 1–16. http://dx.doi.org/10.17485/ijst/2016/v9i47/106900.

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