Optimized Time Management And Scheduling For Users

Disclosed herein is a mobile intelligent scheduling system and method that integrates events, historical conditions and auxiliary data into a series of reminders and automated actions. The system optimizes the entire timeline to meet a set of goals, rather than focusing on a single event, condition or reminder. The system accesses and aggregates schedule information and creates a calendar flow for users that works backward in time and integrates multiple events and conditions. The system alerts or reminds the user with appropriate text messages and integrates the historical data to arrive at optimized time schedules. Alternatively, the system could automatically react to changing conditions and has the additional advantage of being objective, predictive and independent. BACKGROUND While a user is on a business trip and his/her flight departs the next day noon, he/she would want to optimize the schedule for the remaining day and the next day morning including dinner, taxi, a good night's rest, morning coffee, work, and travel to the airport with sufficient arrival time for airport security and check-in (based on typical delays at that time, combined with the priority status, etc). Currently available tools execute portions of the scheduling such as when the user should depart accounting for traffic. However, a user’s sleep preferences and habits while traveling should also be factored into when he/she should go to bed and get up, which in turn would affect other portions of the schedule. Thus, a user requires a mobile device that automatically schedules appropriate alarms/reminders for the user at each stage, based on an optimal schedule, working back from specific requirements. 2 Klein: Optimized Time Management And Scheduling For Users Published by Technical Disclosure Commons, 2016 DESCRIPTION The disclosure relates to a mobile intelligent scheduling system and method that integrates events, historical conditions and auxiliary data into a series of reminders and automated actions. The system optimizes the entire timeline to meet a set of goals, rather than focusing on a single event, condition or reminder. A schematic of the system is shown in FIG. 1, which illustrates how the system combines user information and external data for intelligent scheduling. A mobile device already records (or has the ability to record) information. For example, it may record the device motion information, device data, such as charging data (e.g. charging patterns), alarm settings, or sound-level activity. This data could be obtained through integration with a wearable health measurement device. Likewise, the devices are aware of the device location data (via location history or registered locations). Information regarding how they commute can be obtained via velocity and GPS data. The event data, (e.g. appointment data, reservation data), can be accessed via a calendar app or scraped emails. The travel data could be obtained from emails using a scraping application. In this system, such data can be combined with external data in the manner shown in Figure 1. Such external data can comprise: 1. Traffic and anticipated traffic for the travel data. 2. Flight times, delays, length of security lines. 3. Distance (time and space) between car rental and airport security, security and gates, etc. 4. Taxi availability and reservation times. 5. Hours of sleep needed to be productive. 3 Defensive Publications Series, Art. 350 [2016] http://www.tdcommons.org/dpubs_series/350 FIG. 1: System for intelligent optimized scheduling The system creates a calendar flow for the user that works backward in time and integrates multiple events and conditions listed above. The displayed calendar flow would include pertinent times such as: A. Time of flight, boarding time, the planned arrival time at the airport and time required by the user to go through the airport (check-in, security, transit to gate, etc.). B. Time at which the user should depart for the airport from his/her hotel based on GPS and reservation data in email (or other sources), traffic near the time of the flight and known construction delays. If the user has rented a car, then the time it would factor how long it would take to return to the airport and the extra transit time from the rental center to the security line. If the user has taken a cab or public transport then the system would factor in the time required for clearing airport security lines. The system would also factor in whether it was a domestic flight or international (which typically need additional time to