Information Processing for Risk-Based Video Surveillance Targeting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing surveillance techniques face challenges in effectively deploying finite resources across wide areas and time frames, making it difficult to cover all potential crime or accident hotspots.
Innovation Solution
An information processing apparatus that acquires high-risk time and space information, identifies relevant surveillance targets from captured videos, and determines optimal regions and times for intensified surveillance using a time and space identification unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If surveillance resources are deployed across wide areas and time frames to cover all potential hotspots, then the coverage area is improved, but the resource efficiency deteriorates due to finite resources being spread too thin
Solution Approach 1:
The system performs preliminary analysis by predicting high-risk time and space information before actual surveillance operations. By pre-identifying areas and time slots with high probability of crimes or accidents based on historical data and AI algorithms, the system enables proactive resource deployment rather than reactive response, resolving the contradiction between comprehensive coverage and resource efficiency
Solution Approach 2:
The system applies local quality by differentiating surveillance intensity across different spatial regions and time periods. Instead of uniform coverage, it concentrates resources on specific high-risk areas identified through prediction models, while reducing or eliminating surveillance in low-risk areas, thereby optimizing resource allocation for maximum effectiveness
2Reliability
If comprehensive surveillance is conducted across all predicted high-risk areas and times, then the detection capability is improved, but the processing load increases beyond manageable levels
Solution Approach 1:
The system extracts and processes only the most critical information by filtering video data through AI-based prediction models. It identifies and prioritizes specific time slots and spatial regions with highest risk probability, extracting only those segments for detailed analysis rather than processing all surveillance footage, thus maintaining high detection capability while reducing processing load to manageable levels
Solution Approach 2:
The system segments the surveillance task into multiple manageable components: prediction model generation, risk assessment, target identification, and resource allocation. By dividing the complex surveillance operation into discrete analytical steps processed by different system modules, it reduces the processing load on individual components while maintaining overall detection effectiveness
Data Source
AI summary
An information processing apparatus (10) includes a time and space information acquisition unit (110) that acquires high-risk time and space information indicating a spatial region with an increased possibility of an accident occurring or of a crime being committed and a corresponding time slot, a possible surveillance target acquisition unit (120) that identifies a video to be analyzed from among a plurality of videos generated by capturing an image of each of a plurality of places, on the basis of the high-risk time and space information, and analyzes the identified video to acquire information of a possible surveillance target, and a target time and space identification unit (130) that identifies at least one of a spatial region where surveillance is to be conducted which is at least a portion of the spatial region or a time slot when surveillance is to be conducted, from among the spatial region and the time slot indicated by the high-risk time and space information, on the basis of the information of the possible surveillance target.