Building Risk Analysis System with Geographic Scoring
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Solution Overview
Problem
Current building security systems face challenges in efficiently processing and analyzing the high volume of data from various sources, leading to a need for extensive resources and personnel to manage alarms related to threats, which can be overwhelming due to the dynamic nature of activities and the complexity of integrating diverse data types.
Innovation Solution
A building risk analysis system that processes threats by determining threat categories, calculating risk scores based on geographic areas, and filtering anomalies, utilizing normalization algorithms and machine learning models to prioritize alarms and enhance situational awareness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a security platform processes all threat data from multiple sources, then comprehensive threat monitoring is achieved, but resource consumption and operational complexity increase significantly
Solution Approach 1:
The patent segments the monolithic security platform into modular components: data ingestion service, geofence service, and risk analytics pipeline. Each component handles specific tasks independently, reducing operational complexity while maintaining comprehensive monitoring capabilities. The segmentation allows parallel processing and independent scaling of different functional modules.
Solution Approach 2:
The patent introduces intermediary services between data sources and the core analysis system. The data ingestion service acts as a mediator that standardizes and filters incoming threat data from multiple sources before processing. The geofence service serves as an intermediary layer that pre-processes location data and identifies relevant geographic boundaries, reducing the computational burden on the risk analytics pipeline.
2Measurement precision
If security operators manually review all alarms and threats, then thorough analysis is possible, but the number of required personnel increases
Solution Approach 1:
The system implements self-service through automated risk scoring and anomaly detection algorithms. The risk analytics pipeline automatically calculates risk scores for geographic areas based on threat data patterns, and the system identifies anomalous threats without human intervention. This automation maintains high analysis accuracy while eliminating the need for large numbers of manual reviewers.
Solution Approach 2:
The patent transforms qualitative threat assessments into quantitative risk scores through parameter changes. By converting diverse threat data into standardized numerical scores based on frequency, severity, and geographic distribution, the system enables automated comparison and prioritization. This parameter transformation allows algorithmic processing while preserving the precision needed for accurate threat analysis.
3Speed
If the system processes high volume of threat data in real-time, then response time improves, but computational resources required increase
Solution Approach 1:
The patent performs preliminary actions by pre-defining geofences and pre-processing threat data as it arrives. The geofence service pre-establishes geographic boundaries and pre-filters threats based on location before they reach the risk analytics pipeline. This preliminary processing reduces the computational workload during real-time analysis while maintaining fast response times.
Solution Approach 2:
The system applies partial processing by focusing computational resources on the most critical aspects of threat analysis. Rather than analyzing every detail of every threat equally, the risk analytics pipeline prioritizes calculating risk scores for geographic areas with higher threat frequencies or severities. This selective processing reduces overall computational resource consumption while maintaining effective real-time monitoring.
Data Source
AI summary
A building risk analysis system including one or more memory devices storing instructions thereon, that, when executed by one or more processors, cause the one or more processors to receive threats, each of the threats including a location, wherein each of the threats are threats of a particular threat category, determine a number of threats for each of geographic areas based on the location of each of the threats, and generate a distribution based on the number of threats for each of the geographic areas. The instructions further cause the one or more processors to determine a risk score for each of the geographic areas based on one or more characteristics of the distribution and the number of threats for each of the geographic areas.