Aeris Communications, Inc.

Anupam Bagchi

Subramanian Balakrishnan

Hector Aquiles Rodriguez

Yixiang Chen

Drew S Johnson

Jins George

Fumito Kayama

Santosh Astagi

Anil Goel

In one example embodiment, a computer-implemented method and system for learning places of interest are disclosed. The method includes learning and storing location information of at least one mobile device; detecting a location where no movement of the at least one mobile device has occurred over a pre-determined duration of time; determining whether the detected location is classified as a location of interest based on a predefined criteria; and clustering the learned location of interest into bigger groups based on location information of the learned location of interest using a pre-defined criteria.

Learning locations of interest using IoT devices

A computer-implemented method and system for monitoring route compliance of moving devices are disclosed. The method for monitoring route compliance of moving devices includes determining parameters for a typical trip based on job description; defining compliance parameters for route compliance based on the determined parameters for the typical trip; comparing parameters of the trip for which compliance is to be determined to the defined compliance parameters; and determining if the trip for which compliance is to be determined falls within the defined compliance parameters.

System and method for determining compliant routes for repetitive trips

A computer-implemented method and system for providing a geo-fence are disclosed. The method for providing a geo-fence includes collecting and storing route information for one or more mobile devices; analyzing the route information for the one or more mobile devices to determine optimum route; and creating the geo-fence around a route to be monitored based on the route information for the optimum route. The system for providing a geo-fence includes one or more mobile devices, a user interface and a data processing system. The data processing system includes a learning database, wherein the learning database collects and stores route information for the one or more mobile device; and an analytics engine, wherein the analytics engine analyzes the route information to determine optimum route, and create the geo-fence around a route to be monitored based on the route information for the optimum route.

Learning common routes and automatic geofencing in fleet management

The present invention relates generally to providing a system and method for monitoring devices relative to a learned geographic area using an enablement platform for building web sites and web applications using data storage, management and publication capabilities of hosted web services. The system and method for monitoring M2M devices relative to a learned geographic area (geofence) are built on existing AerCloud concepts by configuring a geofence by using learned location attributes and evaluating geofence parameters and issuing alerts if the devices are performing outside the geofence parameters.

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San Jose, CA, United States of America

Anupam Bagchi