Multi-Modal Entity Tracking System with Modular Data Correlation
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Solution Overview
Problem
Current tracking systems primarily focus on time and location, failing to provide detailed information necessary for effective tracking and analysis of entities such as people, animals, and objects, which is crucial for both immediate and future applications, especially in emergency situations or for optimizing processes like livestock management and package tracking.
Innovation Solution
A method and system for generating, storing, and accessing data relevant to entities, including location, time, image, and biometric information, which allows for decryption, viewing, manipulation, sharing, and analysis, using a server-based system with automated search capabilities and data correlation, enabling detailed tracking and data utilization across various platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If tracking systems only focus on time and location data, then the system complexity is reduced and ease of operation is improved, but the quantity of information and measurement precision are insufficient for effective tracking and analysis
Solution Approach 1:
The tracking system is segmented into multiple independent data collection modules (GPS location, biometric sensors, image capture, text input) that can function separately but integrate to provide comprehensive tracking information. This allows the system to gather detailed information without requiring all components to operate simultaneously, managing complexity through modular design.
Solution Approach 2:
The mobile device is designed to perform multiple functions: tracking location, collecting biometric data, capturing images, and storing text information. By making the device universal and multi-functional, the system gains access to diverse data types without requiring separate specialized devices for each function, thus improving information detail while controlling overall system complexity.
2Measurement precision
If comprehensive data including biometric and image information is collected, then measurement precision and analysis capability are improved, but the use of energy and device complexity increase
Solution Approach 1:
The system implements periodic data collection rather than continuous collection. Biometric sensors, image capture, and other high-energy components are activated at scheduled intervals or triggered by specific events, allowing the device to conserve energy between measurements while still gathering sufficient detailed information for effective tracking and analysis.
Solution Approach 2:
Different data collection methods are applied based on local conditions and requirements. For example, biometric data may be collected with higher precision when the entity is stationary or in controlled environments, while location tracking continues continuously. Image capture is triggered only when relevant events occur, optimizing energy use by applying measurement precision locally rather than uniformly across all tracking aspects.
3Adaptability or versatility
If data is stored and accessed at multiple locations, then adaptability and information availability are improved, but the loss of time for data transmission and synchronization increases
Solution Approach 1:
The system performs preliminary data synchronization and caching before disconnection events are anticipated. When the mobile device is expected to operate offline, data is pre-synchronized with remote servers and local storage is updated in advance. This preliminary action ensures that data is available immediately upon connection restoration without requiring time-consuming real-time synchronization during critical operations.
Solution Approach 2:
The system introduces an intermediary layer of local storage and caching mechanisms between the mobile device and remote servers. This intermediary allows data to be stored and accessed locally without immediate server communication, reducing transmission time delays. The intermediary synchronizes data asynchronously when connectivity is available, maintaining data accessibility across multiple locations while minimizing the time loss associated with data synchronization.
Data Source
AI summary
A method of tracking an entity includes generating data relevant to the entity at a first location, storing the data at a server, and accessing at least a portion of the data at the first location or at a second location. The data can include location information, time information, image data, text, and/or biometric data. The data can be encrypted, organized, categorized, updated, accumulated with other data, classified, and/or disseminated, and an automated search can include an image feature recognition and facial recognition search. The entity can be a person, an animal, or an object. A communications system includes a processing device and a server that includes an automated search engine. The server can be configured to perform data analysis, such as data grouping.