Abstract: Described herein is a framework for classifying social media inputs. In accordance with one aspect of the framework, one or more social media inputs is acquired from one or more social media platforms. The social media inputs are cleaned to remove redundant elements. One or more features are extracted from the cleaned social media inputs. The social media inputs are classified by a trained classifier into predefined categories using the extracted one or more features.

Abstract: Described herein is a framework for vehicle-to-vehicle communication. In accordance with one aspect, a send message to a receiving driver of a receiving vehicle is generated from a sending end-user device in response to a user event from a sending driver. The send message may be generated to include an image of the receiving vehicle of the receiving driver, and a voice message created by the sending driver. The send message may be sent to a server using the sending end-user device. The send message may further be processed by the server, in which the processing may include identifying the receiving vehicle, searching to find information of a receiving end-user device, and sending the send message to the receiving end-user device if information of the receiving end-user device is found.

Abstract: Described herein is a framework for classifying social media inputs. In accordance with one aspect of the framework, one or more social media inputs is acquired from one or more social media platforms. The social media inputs are cleaned to remove redundant elements. One or more features are extracted from the cleaned social media inputs. The social media inputs are classified by a trained classifier into predefined categories using the extracted one or more features.

Abstract: A method for providing trip planning and route update is provided. The method includes receiving traffic demand data including a plurality of planned trips, each including an origin location, a destination location, a planned route, a planned departure time, and an end time. The method further includes building a traffic prediction model by aggregating the traffic demand data, and generating a traffic prediction for a specified trip. Related apparatus, systems, techniques and articles are also described.

Abstract: Disclosed herein are technologies for facilitating activity tracking In accordance with one aspect, sensor data is received from a wearable device. An activity type associated with a worker is recognized based on the sensor data. A fitness analysis may be performed, based on the sensor data and recognized activity type, to determine a stress level of the worker. One or more suggestions for improving the well-being of the worker may then be generated based on the stress level.

Abstract: Described herein is a framework to monitor mobile application usage. In accordance with one aspect of the framework, sensor data from one or more sensors in a mobile computing device is received. Usage of one or more mobile applications implemented on the mobile computing device may be monitored based on such sensor data to generate monitoring results. A report may be generated based on the monitoring results.

Abstract: Described herein is a framework for vehicle-to-vehicle communication. In accordance with one aspect, a send message to a receiving driver of a receiving vehicle is generated from a sending end-user device in response to a user event from a sending driver. The send message may be generated to include an image of the receiving vehicle of the receiving driver, and a voice message created by the sending driver. The send message may be sent to a server using the sending end-user device. The send message may further be processed by the server, in which the processing may include identifying the receiving vehicle, searching to find information of a receiving end-user device, and sending the send message to the receiving end-user device if information of the receiving end-user device is found.

Abstract: Described herein is a framework to monitor mobile application usage. In accordance with one aspect of the framework, sensor data from one or more sensors in a mobile computing device is received. Usage of one or more mobile applications implemented on the mobile computing device may be monitored based on such sensor data to generate monitoring results. A report may be generated based on the monitoring results.

Abstract: Described herein is a framework for an integrated shopping assistance. In accordance with one aspect, the framework may detect a customer in an establishment. The framework may detect the customer by determining location proximity data of one or more detected customer-registered devices in an establishment. The framework may further perform, based on one or more data sources, image recognition of a captured image of a customer. Information associated to the customer may be retrieved from the one or more data sources. Real-time analytics may further be performed based at least in part on the location proximity data and the retrieved customer information. The framework may present, via a client device, a notification based on the location proximity data, a verification of the customer, the associated customer information, and results of the analytics.

Abstract: Described herein is a framework to facilitate workforce planning and analytics. In accordance with one aspect, profile data of at least one job candidate and job data of at least one job opening are received from multiple data sources. The framework may automatically determine a match score between the job candidate and the job opening. Analytics may be performed based at least in part on the match score, the profile data and the job data. Results of the analytics may then be presented.

Abstract: Described herein is a framework for coordinating transportation. In accordance with one implementation, the framework creates or selects a virtual transportation stand in response to a commuter request. The virtual transportation stand may be created or selected based at least in part on current location information associated with a mobile device. Information associated with the virtual transportation stand may then be provided to the commuter mobile device and a vehicle notification device. The virtual transportation stand may further be removed if it is no longer in demand.

Abstract: Described herein is a descriptive framework to facilitate large scale demand responsive transit. In accordance with one aspect of the framework, one or more trip requests from one or more commuter devices are received. A trip request indicates at least one start location and at least one end location. In addition, vehicle information is received from one or more available vehicles. The vehicle information indicates at least one current location of a vehicle. An adaptive route for the vehicle may be planned based on the one or more trip requests and the vehicle information. Update information of the adaptive route may be communicated to the vehicle and the one or more commuter devices.

Abstract: Described herein is a descriptive framework to facilitate large scale demand responsive transit. In accordance with one aspect of the framework, one or more trip requests from one or more commuter devices are received. A trip request indicates at least one start location and at least one end location. In addition, vehicle information is received from one or more available vehicles. The vehicle information indicates at least one current location of a vehicle. An adaptive route for the vehicle may be planned based on the one or more trip requests and the vehicle information. Update information of the adaptive route may be communicated to the vehicle and the one or more commuter devices.

Abstract: A method for providing trip planning and route update is provided. The method includes receiving traffic demand data including a plurality of planned trips, each including an origin location, a destination location, a planned route, a planned departure time, and an end time. The method further includes building a traffic prediction model by aggregating the traffic demand data, and generating a traffic prediction for a specified trip. Related apparatus, systems, techniques and articles are also described.