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Proactive Management of Maintenance Activity in Home appliances

IP.com Disclosure Number: IPCOM000246986D
Publication Date: 2016-Jul-20
Document File: 4 page(s) / 41K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a system and method to implement proactive maintenance alerts and scheduling for home networked devices based on potential upcoming heavy usage periods as discovered by analyzing configured calendars, social media posts, etc.

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Proactive Management of Maintenance Activity in Home appliances

Home network systems (i.e., smart homes) connect many devices, including home entertainment systems, security and remote monitoring systems, and large appliances. Each device requires periodic maintenance and has a downtime during which that maintenance activity can be performed. The use of certain devices is related. For example, if many users are present in the home, then the heating and cooling systems might have more use, as well as the microwave oven and dishwasher, etc. Weather and outdoor temperatures might also affect the use of home systems.

If any system experiences difficulty that requires unplanned maintenance, then the system might have to be shut down, which not only causes inconvenience, but also hardship or danger (e.g., if medical support devices or security systems are disabled). To avoid unplanned shut-down for system or device maintenance, a method and system for proactive management of maintenance activity in home networking devices is needed.

Remote and centralized maintenance is known in the art and sensors can be used to determine the condition of any appliance/device/engine and relay that information to the appropriate parties. Proactive maintenance based on factors such as upcoming weather, upcoming events for heavy usage, or based on the systematic reading of calendars/tweets/posts is not done. No current solution includes a self-learning aspect.

This disclosure proposes a method and system by which any home network system gathers various points if data related to weather, predicted natural disaster, and upcoming calendar events (i.e., reads configured calendars) in order to determine the perfect time to schedule home maintenance for any appliance. Calendar events that factor into the system's analysis include dates/times that the user is away from home, has a busy schedule, is hosting events, etc. The system does not divulge the information, but simply uses it to enable accurate planning. In addition, the system can read and understand any configured stream of data originating in social media posts. For example, if the user posts, "Can't wait, the twin babies are coming in one week", then the system identifies that the user will be unavailable one week from the current day. This also indicates to the system to anticipate a potentially heavy usage time for the networked home system. As the system learns the preferences and reactions of any user(s) over time, it can to better predict the associated appliance maintenance needs.

The core novelty of the proposed solution is the implementation of proactive maintenance alerts and scheduling for home networked devices based on potential upcoming heavy usage periods as discovered by analyzing configured calendars, social media posts, etc. The system looks ahead on configured business calendars in order to alert the user of a perfect time for home system and appliance service based on a light load a...