IoT Scheduler for Optimal Event Site and Timeslot Selection
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Solution Overview
Problem
Conventional calendar applications are limited in determining optimal timeslots and locations for events involving multiple participants, as they lack access to data on other participants' availability and are location-agnostic, making it difficult to identify suitable sites for events.
Innovation Solution
An IoT-based scheduler that utilizes sensor data for occupancy and location information, along with scheduling data, to identify available timeslots and sites for events, and can adjust existing schedules or reserve sites by communicating with IoT devices and user devices to ensure participant availability and minimize travel distance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional calendar applications are used for scheduling, then basic event timing can be recorded, but the system cannot determine optimal timeslots and locations because it lacks access to participant availability data and location information
Solution Approach 1:
The patent combines multiple data sources including calendar applications, IoT sensors, and location services into a unified scheduling system. The server aggregates participant availability from calendar apps, occupancy status from IoT sensors, and location data from mobile devices to comprehensively determine optimal event times and locations, resolving the information loss problem.
Solution Approach 2:
The scheduling system performs multiple functions: it manages calendar events, monitors site occupancy through IoT devices, tracks participant locations, and automatically determines optimal scheduling decisions. This multi-functional approach enables the system to overcome the limitations of conventional single-purpose calendar applications.
2Measurement precision
If the scheduler uses real-time sensor data to determine optimal sites, then location accuracy improves, but the system complexity increases due to integration requirements with IoT devices and multiple data sources
Solution Approach 1:
The patent introduces a server as an intermediary that centralizes data processing. The server receives occupancy data from IoT sensors, calendar data from participant devices, and location information from mobile apps, then processes all this data to determine optimal event locations. This intermediary architecture manages system complexity by providing a single point of coordination.
Solution Approach 2:
The system employs IoT sensors that automatically monitor and report occupancy status without manual intervention. Participants also self-report their availability through calendar applications and location data through mobile devices. This automated self-service approach reduces the operational complexity of data collection while maintaining high location accuracy.
3Loss of time
If the scheduler optimizes for immediate event timing, then response time improves, but the system must process real-time data from multiple sources which increases computational requirements
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and pre-processing data from IoT sensors and participant calendars before an event request is made. Occupancy status and participant availability are updated in real-time in advance, so when scheduling is needed, the server can quickly query pre-processed data rather than collecting everything from scratch, reducing both response time and computational energy.
Data Source
AI summary
A method can include receiving a request to determine a site and a timeslot for an event that requires attendance by a first and second user. Sensor data can be retrieved in response to the request. The sensor data can indicate a current occupancy of multiple sites and a current location of the first and second user. When the first and second user are available for an immediate timeslot, a first site for the event can be identified based on the sensor data. An upcoming timeslot for the event and a second site can be identified based on scheduling data. The scheduling data can indicate a future occupancy of the sites, a future location of the first and second user, and a future availability of the first and second user. An event notification indicating the site and timeslot for the event can be sent to the first and second user.