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Location Data

Software & Data Management
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The position information and associated metadata generated by RTLS including coordinates (x, y, z), timestamps, tag identifiers, quality indicators, and contextual information. Forms the foundation for all RTLS analytics and applications. Typically stored in time-series databases optimized for temporal queries. Volume can be massive in large deployments.

Digital information describing positions, movements, and related context of tracked assets or personnel. Location data elements include: primary position data (X,Y coordinates or latitude/longitude, Z coordinate for height if 3D, timestamp indicating when position measured), derived data (zone or area identification, speed and direction of movement, distance traveled), asset metadata (tag identifier, asset name/type, assignment information), and quality metrics (accuracy estimate, number of anchors contributing, signal strength, GDOP). Location data formats vary: raw position records (individual timestamped coordinates, high volume), track segments (sequences of positions forming paths), zone transitions (entry/exit events with timestamps and duration), aggregated data (position summaries by time period or zone, reduced volume). Industrial RTLS generates substantial data volumes: 1000 tags at 1 Hz updating positions continuously produces 86 million records daily, requiring 3-5 GB storage with metadata (position, timestamp, tag ID, quality metrics). Over 90 days, accumulates 270-450 GB requiring data management strategy: hot storage (recent 1-7 days in high-speed database for real-time queries), warm storage (8-90 days in optimized columnar database for analytics), cold storage (90+ days in compressed archive for compliance/historical reference), and data retention policies (purging data beyond retention requirements). Location data quality considerations: accuracy (how close to true position), precision (consistency of repeated measurements at same location), update rate (frequency of new positions), completeness (percentage of time tags detected), and latency (delay from actual movement to data availability).

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