Autonomous real-time surveillance system with distributed IP cameras

An autonomous Internet Protocol (IP) camera based object tracking and behaviour identification system, capable of running in real-time on an embedded system with limited memory and processing power is presented in this paper. The main contribution of this work is the integration of processor intensive image processing algorithms on an embedded platform capable of running at real-time for monitoring the behaviour of pedestrians. The Algorithm Based Object Recognition and Tracking (ABORAT) system architecture presented here was developed on an Intel PXA270-based development board clocked at 520 MHz. The platform was connected to a commercial stationary IP-based camera in a remote monitoring station for intelligent image processing. The system is capable of detecting moving objects and their shadows in a complex environment with varying lighting intensity and moving foliage. Objects moving close to each other are also detected to extract their trajectories which are then fed into an unsupervised neural network for autonomous classification. The novel intelligent video system presented is also capable of performing simple analytic functions such as tracking and generating alerts when objects enter/leave regions or cross tripwires superimposed on live video by the operator

Outlier detection techniques for wireless sensor networks: A survey

In the field of wireless sensor networks, those measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are not directly applicable to wireless sensor networks due to the nature of sensor data and specific requirements and limitations of the wireless sensor networks. This survey provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy and a comparative table to be used as a guideline to select a technique suitable for the application at hand based on characteristics such as data type, outlier type, outlier identity, and outlier degree

Advancements In Crowd-Monitoring System: A Comprehensive Analysis of Systematic Approaches and Automation Algorithms: State-of-The-Art

Growing apprehensions surrounding public safety have captured the attention of numerous governments and security agencies across the globe. These entities are increasingly acknowledging the imperative need for reliable and secure crowd-monitoring systems to address these concerns. Effectively managing human gatherings necessitates proactive measures to prevent unforeseen events or complications, ensuring a safe and well-coordinated environment. The scarcity of research focusing on crowd monitoring systems and their security implications has given rise to a burgeoning area of investigation, exploring potential approaches to safeguard human congregations effectively. Crowd monitoring systems depend on a bifurcated approach, encompassing vision-based and non-vision-based technologies. An in-depth analysis of these two methodologies will be conducted in this research. The efficacy of these approaches is contingent upon the specific environment and temporal context in which they are deployed, as they each offer distinct advantages. This paper endeavors to present an in-depth analysis of the recent incorporation of artificial intelligence (AI) algorithms and models into automated systems, emphasizing their contemporary applications and effectiveness in various contexts

Wireless Sensor Networks for Detection of IED Emplacement / 14th ICCRTS: C2 and Agility

14th International Command and Control Research and Technology Symposium (ICCRTS), June 15-17, 2009, Washington DC.This paper appeared in the Proceedings of the 14th International Command and Control Research and Technology Symposium, Washington, DC, June 2009.We are investigating the use of wireless nonimaging-sensor networks for the difficult problem of detection of suspicious behavior related to IED emplacement. Hardware for surveillance by nonimaging-sensor networks can cheaper than that for visual surveillance, can require much less computational effort by virtue of simpler algorithms, and can avoid problems of occlusion of view that occur with imaging sensors. We report on four parts of our investigation. First, we discuss some lessons we have learned from experiments with visual detection of deliberately-staged suspicious behavior, which suggest that the magnitude of the acceleration vector of a tracked person is a key clue. Second, we describe experiments we conducted with tracking of moving objects in a simulated sensor network, showing that tracking is not always possible even with excellent sensor performance due to the illconditioned nature of the mathematical problems involved. Third, we report on experiments we did with tracking from acoustic data of explosions during a NATO test. Fourth, we report on experiments we did with people crossing a live sensor network. We conclude that nonimaging-sensor networks can detect a variety of suspicious behavior, but implementation needs to address a number of tricky problems.supported in part by the National Science Foundation under the EXP Program and in part by the National Research Council under their Research Associateship Program at the Army Research Laborator

Contemporary Affirmation of Machine Learning Models for Sensor Validation and Recommendations for Future research Directions

Wireless Sensor Networks (WSNs) are important and needed systems for the future as the notion "Internet of Things" has emerged lately. They're used for observation, tracking, or controlling of several uses in sector, health care, home, and military. Yet, the quality of info collected by sensor nodes is changed by anomalies that happen because of various grounds, including node failures, reading errors, unusual events, and malicious assaults. Thus, fault detection is a necessary procedure before it's used in making selections to make sure the quality of sensor information. A multitude of methods can be called multiple-changeable systems/agents. For example methods such as for example creating heating system, ventilation and air conditioner(HVAC) methods are changeable methods / agents . Multiple-changeable methods /agents such as for instance these commonly don't meet performance expectations imagined at design time. Such failings can be a result of a number of factors, for example difficulties due to improper installment, substandard maintenance, or products failure. These issues, or "faults," can comprise mechanical disappointments, management difficulties, design mistakes, and improper operator treatment