Drone Pre-Surveillance Using Predicted Occupant Movement
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Solution Overview
Problem
Current monitoring systems lack the ability to perform on-demand pre-surveillance of property areas without detecting alarm events and require manual navigation of drones to specific sensor locations, which can be inefficient and may not effectively deter potential trespassers or threats.
Innovation Solution
A monitoring system that uses drones equipped with sensors and AI to learn user behavior patterns, allowing for pre-surveillance of specific areas based on predicted user movements, including indoor and outdoor locations, and assess safety levels by identifying loitering persons, weapons, or other safety threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual navigation of drones to sensor locations is used, then the system can perform surveillance, but the process is inefficient and requires constant human intervention
Solution Approach 1:
The system performs preliminary actions by learning user behavior patterns in advance and proactively dispatching drones to predicted locations before users actually arrive. This eliminates the need for manual navigation and real-time human intervention, as the drones autonomously position themselves based on pre-learned patterns.
Solution Approach 2:
The monitoring system serves itself by automatically learning behavior patterns, making decisions about where surveillance is needed, and dispatching drones without human intervention. The system autonomously manages the entire surveillance process from pattern recognition to drone deployment.
2Reliability
If constant law enforcement surveillance is maintained, then safety is improved, but the cost and resource requirements increase significantly
Solution Approach 1:
The system performs preliminary surveillance actions by proactively monitoring predicted threat locations before incidents occur. This preventive approach maintains high safety levels by detecting potential threats early, reducing the need for constant heavy law enforcement presence.
Solution Approach 2:
The system changes the operational parameters of surveillance by transitioning from constant, uniform monitoring to dynamic, demand-based surveillance. Drones are deployed selectively based on learned patterns and real-time conditions, optimizing resource utilization while maintaining safety.
3Area of stationary object
If drones are dispatched to all potential locations, then comprehensive surveillance is achieved, but the time and energy consumption increase
Solution Approach 1:
The system applies local quality by concentrating surveillance resources in specific locations where threats are predicted based on learned user patterns. Instead of uniform coverage, drones are strategically deployed to high-priority areas, achieving effective surveillance with reduced time and energy expenditure.
Solution Approach 2:
By learning user behavior patterns in advance, the system preliminarily identifies which areas require surveillance. This allows drones to be pre-positioned or quickly dispatched only to predicted locations, reducing response time while maintaining comprehensive coverage of critical areas.
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.