Development of Intelligent,
Geospatial Information-based Security Technologies
Research Fellow, Department of Future Technology and Convergence Research
The central and local governments are providing a number of diverse security services to prevent and deal with various crimes. These security services make use of spatial information to provide basic crime reporting, real-time location and emergency dispatch functions. But certain limitations to these security services are evident, including the difficulty in obtaining precise spatial data, errors in spatial data, discontinuities between indoor and outdoor spatial data, and insufficient interfacing with CCTV systems. To address these limitations, research was conducted to enable precise user location information to be obtained using spatial data technology, to implement intelligent CCTV video processing, to analyze high crime rate areas, and to liaise with the competent authorities in the event of crimes.
The Ministry of Land, Transport and Infrastructure has commissioned research for the development of smart crime prevention technologies based on spatial information technology, and is working to implement a social safety net for the prevention of sex crimes as part of a multi-ministry project. As part of its research for these two projects, KICT has begun its “research project for development of intelligent, geospatial information-based security technologies.”
The aims of the research project are as follows: to improve social safety networks and infrastructures using geospatial information to ensure safety in the everyday lives of the public; to use existing spatial data research to develop cutting-edge technologies so that more effective safety and crime prevention services can be furnished; and, to build a trial zone for the pre-commercialization testing of these new technologies. Given these aims, the project's objectives are as follows: to develop precision location-determining technologies and supporting technologies for the implementation of public safety infrastructure and services; to develop spatial data-based intelligent crime prevention services technology interfaced with CCTV systems in order to implement a crime-preventing social safety network; and, to implement and operate a spatial data-based intelligent crime prevention technology trial zone to fully test these new technologies before providing them to the public.
The present text will discuss some of the component technologies of spatial data-based intelligent crime prevention technology.
[Figure 1] Composition of spatial data-based intelligent crime prevention technologies
(Pic will be added soon)
Precision location-determining technologies
Technology was developed to enable services that provide precision smartphone-based positioning for the socially vulnerable, anywhere and at any time. Significantly, this newly developed technology uses correction data to provide precise location data in “shadow” areas and areas with poor reception, such as narrow alleyways.
To this end, GPD data and correction data received from base stations are used to generate correction and parameter data in the DGPS correction data-generating server, shadow area correction data and parameter-generating server and Assisted-GNSS parameter-generating servers at local government control centers. The generated data and parameters are used to provide users with precision real-time Internet positioning services. Users are able to promptly determine initial user position through A-GNSS data received through the Internet, and the DGPS correction data received together is used to obtain highly precise and highly reliable position data. This means that even when DGPS information cannot be received in areas with poor reception, the shadow area correction data and parameters previously received can be employed to allow the continued use of DGPS services.
While existing indoor positioning technologies use a single signal or two-to-three signals at most, the present study has developed technology that harnesses all available indoor and outdoor signals as a composite signal to build data. Deep learning techniques are applied to this data to produce a combined indoor and outdoor position-determining technology with 30% greater accuracy than existing technologies.
Technology for smart crime-prevention services interfaced with CCTV systems
While local governments are continuing to install and operate CCTV systems, conventional image analysis techniques are prone to misidentification due to reflective surfaces and shadows. Also, they do not provide accurate three-dimensional analyses (position and area detection) of detected objects. To address this problem, real-time background space/moving object separation and tracking technology using stereo video was developed together with a three-dimensional image analysis program and map-based monitoring viewer, allowing for an effective analysis and control system to be provided. For a combined analysis of feeds from multiple CCTV units, a cooperative multi-CCTV spatial data-based tracking and control system was developed. Cooperative CCTV technology is able to quickly learn images of a selected suspect in CCTV feeds. When the suspect moves out of the frame and into the field of view of another CCTV unit, the system informs the controller intuitively of how similar a person detected on the new CCTV unit is to the selected suspect.
In addition, a crime prevention information service was developed that is able to display comprehensive crime information within an area. The crime prevention information service shows neighborhood safety facilities (police stations, fire stations, patrol divisions, neighborhood safety facilities) on a map. Using the CPTED technique, a safety index is assessed for parks, and parks are classified according to the level of safety.
[Figure 2] Overview: DGPS system for precision outdoor position determination
(Pic will be added soon)
Consolidated intelligent crime prevention operation system
The combined intelligent crime prevention operation system was developed as a tool to provide precision location-determining technologies and intelligent CCTV-interfaced crime prevention services to the public. The system uses service scenarios for each of the technologies,
interfacing services which can be operated in integration and enabling local governments to operate them directly. The combined operation system is comprised of a web service operated at local governments’ control centers, and a mobile service for use by the general public.
Technologies to prevent and cope with crime were developed to incorporate spatial data, an important element of state information. The socioeconomic cost of crime is increasing every year, and there is a rising global interest in the implementation of safety systems for women, senior citizens, children and other socially vulnerable individuals. By harnessing low-cost DGPS services and interfacing these with the continuously-growing number of CCTV systems, existing public safety services can be qualitatively improved. By interfacing with existing social safety infrastructure, the technologies developed can be used for crime-related data collection and monitoring, as well as for smart city crime prevention solutions. Other applications for the technologies will include: manpower and materials monitoring at construction sites, parking lot navigation systems for car sharing services, and disaster response in tunnels and underground spaces.
• KICT (May 2019), Presentation Materials from Working-level Smart City Round Table for Local Governments
• Ministry of Land, Transport and Infrastructure (September 2019), Final Report, Development of Spatial Data-based Intelligent Crime Prevention Technologies for Public Safety
[Figure 3] Configuration of positioning technology using multiple composite signals