IoT Predictive Maintenance Herald

The project, 'IoT Predictive Maintenance Herald', draws inspiration from the prophetic nature of the Shrike in Dan Simmons' 'Hyperion', offering users early warnings of potential appliance failures. It combines this with the automated, machine-dependent society depicted in Fritz Lang's 'Metropolis,' highlighting the reliance on smoothly functioning systems. The core concept is to create a low-cost, easily deployable IoT system that monitors the performance of common household appliances (e.g., washing machines, refrigerators, HVAC systems) using readily available sensors (e.g., vibration sensors, temperature sensors, current sensors). These sensors collect data that is then fed into a machine learning model, trained on historical data and publicly available appliance failure information. This model learns patterns indicating imminent failure. The 'Herald' system then provides users with timely alerts and personalized maintenance schedules, preventing costly repairs and extending appliance lifespan. The AI Workflow for Companies scraper inspiration comes in the form of a streamlined process. First, publicly available maintenance data is scraped. Then, the data is cleaned, processed, and fed into the AI model. The system sends alerts through a mobile app or web interface, offering suggestions for preventative maintenance actions. The earning potential lies in a subscription-based service, offering tiered plans based on the number of appliances monitored and the level of support provided. Potential niches include focusing on specific appliance types (e.g., HVAC systems for small businesses) or targeting specific demographics (e.g., elderly homeowners who may not be tech-savvy). The low cost is ensured by using inexpensive sensors and leveraging open-source machine learning libraries.