Abstract:
In the past few decades, crime rate has increased at a great pace in Pakistan. Law and order situation of the country is deteriorating day by day. Every day there are thousands of cases reported about different crime like kidnapping for ransom, murders, robberies etc. More terrifying fact is that most of the cases go unrecorded and unreported. Even worse thing is that out of those cases that are reported mostly goes uninvestigated. Problem lies in the tools, methodologies and techniques used by Pakistan’s Law Enforcement Agencies.
Main challenge that agencies are facing is the lack of digitized criminal investigation system. They still use manual book/record keeping system. FIRs are written manually on registers. There are no centralized data centers. No two agencies can inter-communicate data without facing a lot of hurdles. Old and traditional techniques of crime investigation like taking photographs of the crime scene, tagging, evidence collection, talking to the eye witnesses etc. are still in practice. In fact these are the only techniques that are in practice by Pakistan’s Law Enforcement Agencies.
CISS is base framework that provides solution to all these problems. It offers inter-communication capability between different data stores, automated Crime Patterns Recognition along with digitized profiles and data for Investigators and Convicts. In short, CISS provides adequate number of functionalities that can solve the problems that Law Enforcement Agencies of Pakistan are facing.
By allowing seamless intercommunication between different data stores, CISS aids in overcoming the hurdles faced by agencies in coordinating and transferring data. CISS automates the process of crime patterns recognition. Recognizing the pattern is like connecting the dots in the puzzle, it narrow downs the pool of suspects and gives direction in which to proceed. Machine learning algorithms are used by the framework for clustering crime records/ data on the basis of certain features and characteristics.
