Intergovernmental Cooperation in the Provision of Public Safety: Monitoring Mechanisms Embedded in Interlocal Agreements

2015 ◽  
Vol 75 (3) ◽  
pp. 401-410 ◽  
Author(s):  
Simon A. Andrew ◽  
Jesseca E. Short ◽  
Kyujin Jung ◽  
Sudha Arlikatti
2014 ◽  
Vol 1028 ◽  
pp. 257-261
Author(s):  
Xi Zhu Zhang

With the continuous development of video detection technology, the video analysis technology based on campus security has become an important part of the construction of safe campus. As the college students still are a group that has poor ability of security protection, campus security issue is closely related to the stability of society and family happiness, and has become a topic of concern to the whole society. The intelligent vision-based campus public safety monitoring system is an important means to achieve security monitoring, it can automatically analyze the video image sequence, and detect, track and identify objects in the monitoring scene without human intervention, and make high-level understanding and analysis of behaviors on this basis. Most of the existing visual monitoring systems can collect and store video data, and the real-time event detection task can automatically be generated through background analysis. Intelligent visual monitoring system should not only be used for accident investigation, but also be used to prevent potential disasters and accidents. The system is consisted of system management platform, event mining and analysis, monitoring and extraction of moving targets, forecasting and tracking targets. The paper makes an in-depth study on the application of intelligent visual detection technology on campus. Based on the intelligent visual video analysis, hidden Markov model is adopted in the paper for video event detection and analysis, motion features and shape features are taken as the observation data, and segmentation method is adopted to analyze the influence of video viewing height and angle on the detection result.


Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1391
Author(s):  
Emmanuel Lule ◽  
Chomora Mikeka ◽  
Alexander Ngenzi ◽  
Didacienne Mukanyiligira

Fire monitoring in local urban markets within East Africa (EA) has been seriously neglected for a long time. This has culminated in a severe destruction of life and property worth millions. These rampant fires are attributed to electrical short circuits, fuel spillages, etc. Previous research proposes single smoke detectors. However, they are prone to false alarm rates and are inefficient. Also, satellite systems are expensive for developing countries. This paper presents a fuzzy model for early fire detection and control as symmetry’s core contribution to fuzzy systems design and application in computer and engineering sciences. We utilize a fuzzy logic technique to simulate the performance of the model using MATLAB, using six parameters: temperature, humidity, flame, CO, CO2 and O2 vis-à-vis the Estimated Fire Intensity Prediction (EFIP). Results show that, using fuzzy logic, a significant improvement in fire detection is observed with an overall accuracy rate of 95.83%. The paper further proposes an IoT-based fuzzy prediction model for early fire detection with a goal of minimizing extensive damage and promote intermediate fire suppression and control through true fire incidences. This solution provides for future public safety monitoring, and control of fire-related situations among the market community. Hence, fire safety monitoring is significant in providing future fire safety planning, control and management by putting in place appropriate fire safety laws, policies, bills and related fire safety practices or guidelines to be applied in public buildings, market centers and other public places.


Author(s):  
R. Nicholas Carleton ◽  
Tracie O. Afifi ◽  
Tamara Taillieu ◽  
Sarah Turner ◽  
Rachel Krakauer ◽  
...  

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