Model of Dynamic Routes for Intelligent Police Patrolling (original) (raw)
Related papers
Development of an Intelligent Patrol Routing System Using GIS and Computer Simulations
Using Computer Simulations and Geographic Information Systems
Patrolling in a nonrandom, but focused manner is an important activity in law enforcement. The use of geographic information systems, the emerging real-time data sets (spatial and nonspatial) and the ability via global positioning systems to identify locations of patrol units provide the environment to discuss the concept and requirements of an intelligent patrol routing system. This intelligent patrol routing system will combine available data utilizing Map Algebra and a data structure known as a Voronoi diagram to create a real-time updatable raster surface over the patrolling area to identify destination locations and routes for all patrol units. This information system will allow all patrol units to function “in concert” under a coordinated plan, and make good use of limited patrolling resources, and provide the means of evaluating current patrol strategies. This chapter discusses the algorithmic foundation, implications, requirements, and simulation of a GIS based intelligent p...
Be-safe travel, a web-based geographic application to explore safe-route in an area
In large cities in developing countries, the various forms of criminality are often found. For instance, the most prominent crimes in Surabaya, Indonesia is 3C, that is theft with violence (curas), theft by weighting (curat), and motor vehicle theft (curanmor). 3C case most often occurs on the highway and residential areas. Therefore, new entrants in an area should be aware of these kind of crimes. Route Planners System or route planning system such as Google Maps only consider the shortest distance in the calculation of the optimal route. The selection of the optimal path in this study not only consider the shortest distance, but also involves other factors, namely the security level. This research considers at the need for an application to recommend the safest road to be passed by the vehicle passengers while drive an area. This research propose Be-Safe Travel, a web-based application using Google API that can be accessed by people who like to drive in an area, but still lack of knowledge of the pathways which are safe from crime. Be-Safe Travel is not only useful for the new entrants, but also useful for delivery courier of valuables goods to go through the safest streets.
2014
In the present situation, where every day we come across crimes, it is of prime importance to ensure ones safety and any measure which could ensure ones safety is certain to pay for itself. In this project, we propose a method to find the safest path between two locations, based on geographical models of crime intensities. We consider the police records and news articles as the basis for our calculations. It is essential to consider news articles as there is a significant delay in updating crime records. We address this problem by updating the crime intensities based on current news feeds. Based on the updated crime intensities, we identify the safest path. It is this real time updation of crime intensities which makes our model way better than the models that are presently in use.
Seguridad ciudadana usando algoritmos de aprendizaje no supervisado mediante datos abiertos
Proceedings of the 16th LACCEI International Multi-Conference for Engineering, Education, and Technology: “Innovation in Education and Inclusion”, 2018
The following work applies Machine Learning algorithms as a tool for a possible solution to the problem of citizen security in a South American city. This application aims to reduce the threat risk to the physical integrity of pedestrians through the geolocation, in real time, using safer places to walk. A database of free disposal for the user is the Open Data San Isidro, district of Lima, Peru, which has been used in the development of this work. This database keeps records of different accidents types (most of the automobile type) occurring in different places of this district, this data will be used to determine safe areas in the route from one place to another, decreasing the probability of suffering an accident. For this work, techniques of non-supervised learning algorithms of Clustering type: k-Means have been used. Likewise, a reduction of dimensions has previously been made using the Principal Component Analysis (PCA) technique.
Intelligent route surveillance
Unattended Ground, Sea, and Air Sensor Technologies and Applications XI, 2009
Intelligence on abnormal and suspicious behaviour along roads in operational domains is extremely valuable for countering the IED (Improvised Explosive Device) threat. Local sensor networks at strategic spots can gather data for continuous monitoring of daily vehicle activity. Unattended intelligent ground sensor networks use simple sensing nodes, e.g. seismic, magnetic, radar, or acoustic, or combinations of these in one housing. The nodes deliver rudimentary data at any time to be processed with software that filters out the required information. At TNO (Netherlands Organisation for Applied Scientific Research) research has started on how to equip a sensor network with data analysis software to determine whether behaviour is suspicious or not. Furthermore, the nodes should be expendable, if necessary, and be small in size such that they are hard to detect by adversaries. The network should be self-configuring and self-sustaining and should be reliable, efficient, and effective during operational tasksespecially route surveillance-as well as robust in time and space. If data from these networks are combined with data from other remote sensing devices (e.g. UAVs (Unmanned Aerial Vehicles)/aerostats), an even more accurate assessment of the tactical situation is possible. This paper shall focus on the concepts of operation towards a working intelligent route surveillance (IRS) research demonstrator network for monitoring suspicious behaviour in IED sensitive domains.
Journey to Crime Using Dijkstra's Algorithm
Nigerian Journal of Environmental Sciences and Technology
This paper describes some benefits of crime mapping in a Geographic Information Systems (G.I.S.) environment. The underlining principle of Journey to Crime was discussed. Crime Spots and Police Stations in the study area were mapped, Shortest-Path, Closest Facility, Service Area and OD (Origin – Destination) Cost Matrix were determined based on Dijkstra's Algorithm. Results show that the distribution of police stations does not correspond with the spread of crime spots.
Journal of Transport Geography, 2013
Applying Data-Driven Approaches to Crime and Traffic Safety (DDACTS) can help police departments allocate limited resources more efficiently. By focusing on hazardous areas, highly visible traffic law enforcement can reduce crime and crashes simultaneously. Most studies have focused on the reduction of crime and crashes after applying new patrol routes, but few have documented how to improve or change police dispatch time. The objective of this study was to compare the police dispatch time between two conditions: (1) Police patrol routes with organized hotspots; and (2) Police patrol route patterns without focusing on hotspots. A secondary objective consisted of developing a procedure describes the calculation of the change in dispatch time. This study used data obtained from the College Station Police Department. Crime and crash data were collected between January 2005 and September 2010, which included 65,461 offense reports and 14,712 crash reports. The proposed study procedure included four steps: (1) Geocoding data, (2) defining hotspots, (3) organizing the best patrol routes, and (4) estimating the effectiveness. ArcGIS was used for the data analysis. The results indicated that using DDACTS principles can potentially reduce police dispatch time by 13% and 17% when the top 5 and top 10 hotspot routes are included in the analysis, respectively. The procedure can be used by law enforcement agencies to estimate whether or not the DDACTS protocols can be an effective tool for reducing law enforcement dispatch times when crash and crime data are analyzed simultaneously.
An Intelligent Transportation System: the Quito City Case Study
International Journal on Advanced Science, Engineering and Information Technology
Managing traffic in a large city has become a topic of great interest in both politics and science. The costs of poor traffic management have been quantified as losses equal to millions of dollars, not counting the unquantifiable value of the time that a person loses in traffic jams. Intelligent transport systems (ITS) offer a set of innovative solutions specific to the management of different modes of transport. This article focuses on the development of an ITS for the city of Quito that allows smart decisionmaking to direct heavy haul transporters that want to enter the city via one of its main access routes. Technologies such as Sensor Web Enablement (SWE), in association with the Message Queuing Telemetry Transport (MQTT) communication protocol, facilitate the development of a vehicular management platform/system capable of sending notifications in real-time and issuing instructions to drivers regarding traffic delays along routes, average speeds, etc. The system supports a network of heterogeneous sensors accessible through the web. It can integrate any device that uses HTTP protocol. Time interval and location range testing have been undertaken to refine the accuracy of the system and make it adaptable to any geographic situation. The system allows communicate with the server through MQTT or through web services, using technologies such as: MongoDB and GeoJSON. One of the most relevant results is that the degree of accuracy of the system is within appropriate ranges when compared to commercial applications such as Google Maps and Waze.