AN INTELLIGENT CRIME MANAGEMENT SYSTEM FOR LAFIA METROPOLIS
DOI:
https://doi.org/10.33003/fjs-2022-0603-990Keywords:
Intelligent Crime Management System, web-based, Lafia metropolisAbstract
Security is one of the major concerns in our societies today, and the issues related to it are steadily increasing in both intensity and complication. Predicting crimes could help, but that is a huge challenge as it requires a study of the behavioral pattern or trend of criminal activities. This research aims to develop an Intelligent Crime Management System for the Nigeria Police Force using a case study of Lafia metropolis in Nasarawa State. The java development kit (JDK), android software development kit (SDK), sinch sdk for app-to-app call, android studio, firebase and a virtual emulator, were used to accomplish the research objectives. This system is comprised of an android based mobile application for crime reporting and awareness, a geospatial database that houses both legacy and new crime data, and a web-based intelligent application. The system can utilize the crime data stored in the database to identify hotspots and clusters in the Lafia metropolis. It can also predict the crime likely to occur at a location and analyze risk assessment and situation assessment of crime in Lafia metropolis
References
Ahmad, S. P and Ahmad, K. “Bayesian analysis of weibull distribution Using R Software†Australian Journal of Basic and Applied Sciences, 7(9): 156-164. ISSN 1991- 8178, (2013).
Almaliki, J. Saad and Y. Jingson, “A new modified weibull distributionâ€. Reliab Eng Syst Safe. 2013; Vol. 111(C):164-170. DOI: 10.1016/j.ress.2013.10.018 (2013).
Al Omari, M. A. (2016). Bayesian study using MCMC of Gompertz distribution based on interval censored data with three loss functions. Journal of applied science, ISSN 1812-5654
Bo H., W. C., Xiofeng, D. “Additive modify weibull distributionâ€. Reliability engineering system safety 145:28-37(2016)
Chen, R., and Amin, N.“Maximum product of spacing estimation with application to the lognormal distributionâ€. Mathematical Report 79-1 Cardiff Department of mathematics, UWIST. (1979)
Chen, Z. “A new two parameter lifetime distribution with bathtub-shaped or increasing failure rate functionâ€. Statt probabil Lett. 49:155-161(2000)
Chris. B. G and Noor, A. I. (2012). “Bayesian Analysis of the survival function and failure rate of weibull distribution with censored dataâ€. Mathematical problem in engineering volume 2012, Article ID 329489, doi:10.115/2012/329489 (2012)
Eisa, M., Rahmat, S., Batool, K. and Debasis, K.†Extended exponentaited Weibull (EEW) distributionâ€. Statistica, department of statistics, University of Bologna, Vol. 78(4), pages 365-396 (2018).
Elgarhy, M., shakil, M. and Elgarhy, K. B. “Exponentiated weibull-Exponential distribution (EWED) with applicationsâ€. An international journal of applications and applied mathematics (AAM) Vol. 12 Issue pp. 710-723 (2017).
Govind, S. Mudholkar and Srivastava, D. K. “Exponentiated Weibull family for analyzing Bathtub failure rateâ€. IEEE T Reliab. 1993; 42:299-302. (1993).
Hastings, W. K “Monte Carlo sampling methods using Markov Chains and their applicationsâ€. Biometrika 57, 97-109 (1970).
Hongtao, Z., Tian L. and Qiming C. “Five and four parameter lifetime distribution for bathtub-shaped failure rate using perks mortality equationâ€. Reliability engineering and system Safety Vol 152, August 2016 https://doi.org/10.1016/j.ress.2016.03.014
Kamram, A., Noshen, Y. A., Amjad, A., Sajjad, A. K., Sadaf, M., Alamgir, K., Umar, K., Dost, M. k., and Zamir, H. “Bayesian analysis of three-parameter Frechet distribution with medical applicationâ€. Computational and mathematical methods in medicine Article ID 9089856 (2019)
Lai, C. D, Xie, M and Murthy, D. N. P. “A Modified Weibull distributionâ€. IEEE T Reliab.2003; 52:33-37
Mohammed, K. S., Atur J. L. and Gauss, M.C. “On the generalized extended exponenetiated weibull (GExEW) distributionâ€. An international journal of computer mathematics 97:5, 1029-1057 (2019).
Neetu, S., Kanchan, J., and Suresh, S. “The generalized Weibull distribution: properties, estimation and applicationsâ€. Reliability engineering, system safety (2012), 102:5-15
Romana, S. and Athar, A. K. “Reliability analysis using exponential power model with bathtub-shaped failure rate functionâ€. A Bayes study. Shehla and Khan springerplus (2016) 5:1079
Sarhan, A. M and Joseph, A. “Exponentiated Modified weibull extension distributionâ€. Reliab Eng Syst Safe. 2013; 112:137-144
Sarhan, A.M and Zaindin, M. “Modified weibull (MW) distribution†Applied Science 46N30, 47N30, 65C60, (2000)
Tien, T. T and Radim, B. “An Additive Chen-Weibull distribution and its applications in reliability modelingâ€. A research article (2020). DOI: 10.1002/qre.2740
Vikas, K S., Sanjay, K. S. and Umesh, S. “Classical and Bayesian methods of estimation for power Lindley distribution with application to waiting time dataâ€. Article in communication for statistical application and methods Vol.24, No.3 (2017).
Weibull, W. Investigate in to strength properties of brittle material. Proc. The royal Sweedish for Engr. #149 (1938)
Xie, M and Lai C.D. “Reliability analysis using an additive Weibull model with bathtub shaped failure Rate functionâ€. Reliability engineering (2019).
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