Drone Pre-Surveillance Using Behavior-Based Navigation 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 detecting alarm events, which can lead to inefficiencies and safety concerns.
Innovation Solution
A monitoring system that utilizes drones equipped with sensors and navigation technology to pre-surveil areas by analyzing user behavior patterns, determining drone navigation paths, and transmitting instructions for pre-surveillance based on learned patterns, including indoor and outdoor areas, to identify potential safety threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a monitoring system uses traditional sensor-based surveillance, then it can detect alarm events, but it cannot perform on-demand pre-surveillance of areas users are expected to travel to
Solution Approach 1:
The system performs preliminary surveillance actions by deploying drones to areas users are expected to travel to before the users actually arrive. The monitoring unit determines drone navigation paths based on learned user behavior patterns and transmits instructions for pre-surveillance, allowing the system to proactively identify potential threats before users encounter them.
2Reliability
If the monitoring system continuously surveils all property areas, then it can maintain high security, but it generates excessive energy consumption and operational inefficiency
Solution Approach 1:
The system dynamically adjusts surveillance operations based on learned user behavior patterns. Instead of continuous surveillance, the monitoring unit determines when and where to deploy drones by analyzing user acts and predicting future locations. This dynamic approach maintains high security at the predicted locations while avoiding energy-wasting continuous surveillance of all areas.
Solution Approach 2:
The system uses learned user behavior patterns to automatically determine surveillance needs without constant human intervention. The monitoring unit self-manages drone deployment by analyzing user acts, determining pre-surveillance rules, and autonomously sending navigation instructions to drones, reducing both energy consumption and operational overhead.
3Reliability
If the system deploys drones for pre-surveillance based on user behavior patterns, then it can identify potential threats proactively, but it increases device complexity
Solution Approach 1:
The monitoring unit serves as an intermediary that manages the complexity of coordinating multiple drones and analyzing user behavior patterns. It receives user act data, applies pre-surveillance rules, determines navigation paths, and transmits instructions to drones, thereby centralizing control and managing system complexity while maintaining high threat identification accuracy.
Data Source
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Figure 2A~2B
Figure 2C
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.