Place Recommending Apparatus Using Sensor Data for Real-Time Environment Matching
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Solution Overview
Problem
Users face difficulties in finding places with desired environments in real-time using only reviews or pictures, as existing methods lack real-time environment information collection and recommendation capabilities.
Innovation Solution
A method and apparatus that utilize sensor data from devices to collect environment information, establish a database, and recommend Point of Interest (POI) locations based on user-desired conditions, incorporating sensors like accelerometers, barometers, and thermometers to provide real-time environment data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor data collection and processing system is implemented, then real-time environment information recommendation capability is improved, but device complexity and information processing load increase
Solution Approach 1:
The system is divided into multiple independent components: sensor data collection module, environment information database module, recommendation engine module, and user interface module. Each module performs a specific function, reducing overall system complexity while enabling real-time recommendations through coordinated operation of these segmented components.
Solution Approach 2:
An environment information database acts as an intermediary between sensor data collection and recommendation generation. The database pre-processes and stores environment information from multiple sensors, reducing the processing burden on the recommendation engine and enabling faster real-time recommendations without increasing overall system complexity.
2Measurement precision
If multiple sensors are used to collect environment information, then measurement precision and recommendation accuracy are improved, but device complexity and cost increase
Solution Approach 1:
Data from multiple different sensors (temperature, humidity, noise, light) are merged into a unified environment information record. This combination of multiple sensor types provides comprehensive environment characterization with high measurement precision while sharing processing infrastructure to control complexity.
Solution Approach 2:
The sensor data collection system is designed to accommodate multiple sensor types through a universal data interface and processing framework. This multi-functional architecture allows different sensors to be integrated without proportionally increasing system complexity, as the same processing pipeline handles all sensor data.
3Measurement precision
If environment information database is established using sensor data from multiple devices, then recommendation accuracy is improved, but data processing time and energy consumption increase
Solution Approach 1:
Environment information from sensor data is pre-processed, validated, and stored in the database before actual recommendation requests. This preliminary action prepares the data in advance, reducing processing time when real-time recommendations are needed while maintaining high accuracy through comprehensive pre-collected data.
Solution Approach 2:
The system automatically collects, processes, and updates environment information in the database without requiring manual intervention for each recommendation query. This self-service mechanism maintains accurate recommendation data over time while minimizing additional processing time for each user request.
Data Source
AI summary
A method of receiving a recommendation of Point of Interest (POI) information from a place recommending apparatus is provided. The method includes sending a POI information recommendation request to the place recommending apparatus using sensor data and receiving a recommendation response to the POI information recommendation request from the place recommending apparatus based on user-desired environment information.