ChronoShelf: Temporal Anomaly Detector for Retail Inventory

Inspired by the meticulous log-scraping of security systems in 'Security Logs' projects, the time-bending narrative of 'Nightfall,' and the urgent detection of temporal paradoxes in '12 Monkeys,' ChronoShelf aims to be a niche, low-cost, yet high-potential retail technology. The core concept is to treat retail inventory data (from CCTV timestamps, POS transaction logs, and potentially RFID scans) as a form of 'security log.' The system will ingest these logs and employ simple temporal anomaly detection algorithms. Instead of hunting for saboteurs in the past, ChronoShelf looks for 'anomalies' in the -present- flow of goods. For example, a product appearing on shelves significantly -before- its recorded arrival date, or a stock level dropping drastically without a corresponding sale in the log. This could indicate internal theft, errors in stock management, or even sophisticated shoplifting rings manipulating timing. The 'story' is that of a watchful guardian, similar to the archivists in 'Nightfall' or the desperate mission in '12 Monkeys,' but focused on the temporal integrity of the retail environment. Implementation involves affordable scripting (Python is ideal) to parse log files and basic statistical analysis to identify outliers in timestamps and quantities. The niche aspect is its focus on -temporal- discrepancies rather than just visual theft detection. High earning potential comes from reducing shrinkage, optimizing inventory management, and offering a unique, data-driven security layer to small to medium-sized retailers who can't afford enterprise-level solutions. It’s a 'time detective' for your shelves.