Sensor-Based Device Protection and Proactive Insurance
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Solution Overview
Problem
Computing devices face increased risks of damage or loss due to their portability and complexity, with existing solutions failing to effectively protect them from various hazards such as accidental drops, theft, or environmental conditions.
Innovation Solution
A computer-implemented method that uses sensor data from computing devices to identify potential risks, such as damage or loss, and presents an insurance offer to users, leveraging data from various sensors like thermal detectors, location detectors, and inertial sensors to anticipate and mitigate threats before harm occurs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If computing devices become more capable and portable, then functionality and user convenience are improved, but the risk of damage or loss increases
Solution Approach 1:
The system performs preliminary actions by monitoring sensor data continuously to detect early signs of risky events (drops, exposure to elements, unauthorized removal) before actual damage occurs. Insurance offers are presented proactively upon detection of potential risks, enabling users to secure coverage before harm happens, thus resolving the contradiction between device portability and safety.
2Reliability
If traditional insurance models are used, then coverage is provided after damage occurs, but users face excessive claims and financial loss
Solution Approach 1:
The system implements feedback by continuously monitoring sensor data from computing devices and using this information to dynamically adjust insurance risk assessment. Sensor data provides real-time feedback on device conditions and user behavior, enabling the system to identify at-risk devices and present targeted insurance offers, thereby reducing excessive claims through proactive risk management rather than reactive compensation.
3Measurement precision
If sensor data monitoring is implemented, then risk identification accuracy is improved, but system complexity increases
Solution Approach 1:
The system applies universality by using existing multi-functional sensors already present in computing devices (accelerometers, gyroscopes, environmental sensors, GPS) for insurance risk monitoring. These sensors serve multiple purposes including device orientation, motion tracking, and now risk event detection. This approach improves risk detection accuracy without significantly increasing system complexity, as the sensors and their data collection capabilities are already integrated into the device.
Data Source
AI summary
Embodiments of the present disclosure help protect computing devices by, among other things, identifying events that may pose a risk to a computing device based on data from sensors coupled to the computer device.