Drone Pre-Surveillance Using Learned Occupant Behavior Paths
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Solution Overview
Problem
Current monitoring systems lack the ability to perform on-demand pre-surveillance of property areas based on learned user behavior patterns without triggering an alarm event, which can lead to inefficiencies and potential safety risks.
Innovation Solution
A monitoring system that utilizes drones equipped with sensors and navigation algorithms to pre-surveil areas identified by learned user behavior patterns, determining drone navigation paths and transmitting instructions for pre-surveillance based on user actions and sensor data, allowing for proactive safety assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a monitoring system uses traditional sensor-based surveillance, then it can detect sensor data generated by monitoring system sensors, but it cannot perform pre-surveillance of areas before users actually reach them without triggering an alarm event
Solution Approach 1:
The system performs preliminary surveillance actions by deploying drones to pre-surveil areas before users actually reach them. The monitoring system determines user behavior patterns and proactively sends drone navigation paths to pre-surveil predicted locations in advance, enabling safety assessments before potential threats materialize into alarm events.
Solution Approach 2:
The patent introduces drones as intermediary devices between the monitoring system and the areas to be surveilled. These robotic devices act as mediators that can physically navigate to and surveil target areas without requiring traditional sensor infrastructure at every location, thereby enabling pre-surveillance while maintaining system manageability.
2Reliability
If the monitoring system continuously surveils all property areas, then it can detect potential threats, but it generates excessive alarm events and wastes resources
Solution Approach 1:
The system performs preliminary surveillance only in areas predicted to be visited by users, based on learned behavior patterns. This selective pre-surveillance approach enables threat detection in relevant areas while avoiding continuous monitoring of all property areas, thereby reducing false alarms and resource waste.
Solution Approach 2:
Instead of continuous surveillance of entire properties, the system applies partial surveillance focused only on specific areas where users are predicted to go. This partial action approach provides sufficient threat detection capability while significantly reducing resource consumption and false alarm generation.
3Productivity
If the monitoring system responds to sensor data after alarm events occur, then it can address immediate threats, but it cannot prevent crimes before they happen
Solution Approach 1:
The system determines user behavior patterns and proactively sends drone navigation paths to pre-surveil predicted locations before users arrive. This preliminary action enables the system to detect and potentially prevent crimes before they occur, rather than merely responding after alarm events are triggered.
Solution Approach 2:
The monitoring system continuously learns from user behavior patterns and sensor data to refine its predictions. This feedback mechanism enables the system to improve its pre-surveillance accuracy over time, allowing it to more effectively anticipate user movements and deploy drones to prevent crimes before they happen.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a storage device, for using a drone to pre-surveil a portion of a property. In one aspect, a system may include a monitoring unit. The monitoring unit may include a network interface, a processor, and a storage device that includes instructions to cause the processor to perform operations. The operations may include obtaining data that is indicative of one or more acts of an occupant of the property, applying the obtained data that is indicative of one or more acts of the occupant of the property to a pre-surveillance rule, determining that the pre-surveillance rule is satisfied, determining a drone navigation path that is associated with the pre-surveillance rule, transmitting, to a drone, an instruction to perform pre-surveillance of the portion of the one or more properties using the drone navigation path.