Driving behavior for a particular driver may be gathered and analyzed over a time period, such as a year or a duration of the driver's employment at a particular employer. The driving behavior is received by a server from a positioning device as multiple streams of position data at different time stretches throughout the time period, each stream of position data associated with a route of a plurality of routes driven by at least one vehicle. The server generates speed data from the streams of position data and compares the speed data to retrieved speed limit data for those routes. The server generates a report with at least a speeding percentage value corresponding to how often the driver was speeding while driving during the time period. The report is then sent to the driver's computing device.

A method of operation of a navigation system includes: calculating a speed difference value based on a sensor speed measurement and a location speed measurement; generating a speed probability distribution with the speed difference value and the sensor speed measurement calculating a density regression based on a speed density peak of the speed probability distribution; determining a speed adjustment factor from the density regression; and calculating an adjusted sensor speed from the sensor speed measurement with the speed adjustment factor.

Methods, systems and computer program products to detect distracted driving are disclosed. A mobile device is associated with a vehicle driver. Suspect activity associated with the vehicle driver is detected based at least in part on mobile device use data collected by the mobile device. A suspect activity record is generated comprising mobile device use data associated with the detected suspect activity. The suspect activity record and an identifier of the vehicle driver are provided to a repository.

Presented are a recording apparatus, a mobile terminal, an analysis apparatus, a program, and a storage medium that can detect a slight tendency toward change in step length and walking speed with high accuracy. The recording apparatus includes: a mobile terminal; and an analysis apparatus, wherein the mobile terminal includes a positioning device and a sensor, acquires position information of the mobile terminal from the positioning device, acquires, from the sensor, measurement information indicating whether a walker is walking straight on a flat, extracts position information of a case where the walker is walking straight on the flat from among pieces of the position information, on the basis of the measurement information, and calculates a walking speed and a step length of the walker, on the basis of the extracted position information, and the analysis apparatus notifies the walker of changes in walking speed and step length.

A handheld or mountable air measuring device includes a sensor assembly with sensors that measure airspeed simultaneously in two directions that are perpendicular to each other. The device includes a data protocol conversion board allowing the communication between the sensor assembly and a smart device included with or associated with the device. The smart device receives the airspeed data. The smart device includes a user interface that includes a map or layout of the environment within which the device is used. The data is displayed on the smart device on the map. The data can be processed locally or transmitted to a remote location for processing. One or more dashboards are generated from the data and accessible by the smart device or another computing device.

Disclosed is a system and method of two-way wireless-communication of vehicular status with one or more different recipient computer servers operated by one or more third parties to promote safer driving. The wireless-communication is based on the low-power, wide-area communication technology, particularly Random Phase Multiple Access (RPMA) communication network. The system consists of a device connected to an On-board diagnostics (OBD) port on the vehicle and onboard sensors whose data are locally processed to provide guidance to the driver. The device utilizes an audio unit, a display unit, and/or a combination thereof to warn about a potential hazard. The device further includes a plurality of sensors to sense the plurality of events. Further, On-Board AI connector, wherein the device communicates with external systems installed in the vehicle ex: camera or other sensor to record and/or analyze human behavior in detail and report drowsy driving, distracted driving, usage of mobile phones or other devices while driving etc. when the driver is recognized to be in one of these states the device plays an appropriate audio message to alert the driver.

An omni-directional anemometer may include a housing, a cavity, and a plurality of ports in fluid communication with the atmosphere. The ports may include at least one sensor configured to measure air pressure. The robust housing may be formed by additive manufacturing, casting, machining, or molding. The anemometer may include a controller configured to determine wind speed and direction using the air pressure measurement signals from the at least one sensor. The anemometer may include a communication module configured to send and/or receive signals from the at least one sensor and the controller using wired and/or wireless communication. The communication module may send or receive signals to or from a network, a server, a vehicle, a structure, and/or a user interface. The anemometer may include a power supply connected to the at least one sensor, controller and/or communication module.

A method of determining airspeed of a movable object includes performing a calibration process to determine a relationship between forces exerted on the movable object and airspeed of the movable object, determining forces exerted on the movable object while the movable object is moving, and determining an airspeed of the movable object based on the determined forces and the relationship.

Methods, systems and computer program products to detect distracted driving are disclosed. A mobile device is associated with a vehicle driver. Suspect activity associated with the vehicle driver is detected based at least in part on mobile device use data collected by the mobile device. A suspect activity record is generated comprising mobile device use data associated with the detected suspect activity. The suspect activity record and an identifier of the vehicle driver are provided to a repository.

A method and system for detecting unsafe or suspect activities such as distracted driving associates distracted driving events to the road type, vehicle speed and vehicle acceleration (positive, negative and lateral) at the time of the distracted driving event, and identifies severe distracted driving events from a large population of minor events using a statistical distribution such as a Cauchy distribution equation. The system employs a smartphone application (App) coupled with a central server that computes driver safety scores which relate time of day, road type, vehicle speed, vehicle acceleration (positive, negative and lateral) and distracted driving using the Cauchy distribution equation. The server renders summary and detail reports of driving scores and distracted driving events to concerned parties including insurance companies, fleet managers, vehicle owners and the parents/guardians of teenaged drivers.