Automatic Electronic Journal Generation from GPS and Media Data
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Solution Overview
Problem
Existing electronic journal systems require manual compilation and are not suited for portraying a sequential series of events, making it difficult for readers to discern the sequence and relationship between events, especially when using disparate data sources like digital cameras, GPS, and social networks.
Innovation Solution
A computer-implemented method that receives GPS location data and other recordings, extracts metadata, correlates it with travel routes to generate travel events, and displays these events on an interactive map with a chronological storyline, integrating data from various sources automatically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual compilation is used to create electronic journal entries, then the author can carefully select and organize content, but the process requires a great deal of manual effort and time
Solution Approach 1:
The system automatically collects data from multiple sources (GPS devices, digital cameras, social networks), extracts relevant information, and generates journal entries without requiring manual input from the author. The system serves itself by autonomously navigating through disparate data sources, selecting appropriate content, and formatting it into coherent narrative entries.
Solution Approach 2:
The system performs preliminary data collection and processing by automatically gathering data from various sources before the author needs to create the journal. It pre-processes the data by extracting metadata, determining travel routes, and organizing content into potential entries, so that when the author views the journal, the work is already prepared and merely needs review.
2Ease of operation
If a blog format is used to record events, then the author can easily post updates, but the format is not suited for portraying a realistic narration of sequential events and requires readers to scroll through entries to discern sequence and relationships
Solution Approach 1:
The system merges multiple data sources (GPS location data, digital images, videos, text messages, social network posts) into a unified chronological narrative. It combines disparate entries into a cohesive story that maintains the sequence of events and their relationships, presenting them in an integrated format rather than separate blog posts.
Solution Approach 2:
The system adds a temporal and spatial dimension to the event presentation by organizing entries chronologically and geographically along the travel route. It presents events in the order they occurred and their spatial relationships, creating a multi-dimensional narrative structure that provides context about sequence and location without requiring readers to scroll through a single-dimensional blog feed.
3Reliability
If data from multiple disparate sources is manually integrated, then the author can carefully select relevant information, but the process is time-consuming and complex
Solution Approach 1:
The system replaces the mechanical process of manual data collection, extraction, and integration with automated computer processing. It uses algorithms to navigate through disparate data sources, extract relevant metadata and content, and organize it into coherent entries. The mechanical action of manually sorting through files and sources is substituted with automated software processing that achieves the same reliability of data selection much faster.
Data Source
AI summary
A system and method of the subject technology automatically generates an electronic journal of a series of events based on input from data sources already used to record the series of events, and then displays those events in an electronic publication representative of the series of events. A GPS track may be used in connection with the series of events to generate the electronic journal in connection with an interactive map.