Enables integration of sensor data with other information on servers such as social media sites to detect, confirm and/or publish events. Sensors may measure values such as motion, temperature, humidity, wind, pressure, elevation, light, sound, or heart rate, etc. Sensor data and event tags may be utilized to curate text, images, video, sound and post the results to social networks, for example in a dedicated feed. Event tags generated by the system may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags. The system may create highlight and fail reels filtered by metrics and by tags. Recommendations may be provided to a user based on analysis of sensor data and other information; recommendations may include for example recommended friends, purchases, or activities.

A system that analyzes data from multiple sensors, potentially of different types, that track motions of players, equipment, and projectiles such as balls. Data from different sensors is combined to generate integrated metrics for events and activities. Illustrative sensors may include inertial sensors, cameras, radars, and light gates. As an illustrative example, a video camera may track motion of a pitched baseball, and an inertial sensor may track motion of a bat; the system may use the combined data to analyze the effectiveness of the swing in hitting the pitch. The system may also use sensor data to automatically select or generate tags for an event; tags may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags.

A system that analyzes data from multiple sensors, potentially of different types, that track motions of players, equipment, and projectiles such as balls. Data from different sensors is combined to generate integrated metrics for events and activities. Illustrative sensors may include inertial sensors, cameras, radars, and light gates. As an illustrative example, a video camera may track motion of a pitched baseball, and an inertial sensor may track motion of a bat; the system may use the combined data to analyze the effectiveness of the swing in hitting the pitch. The system may also use sensor data to automatically select or generate tags for an event; tags may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags.

A system that analyzes data from multiple sensors, potentially of different types, that track motions of players, equipment, and projectiles such as balls. Data from different sensors is combined to generate integrated metrics for events and activities. Illustrative sensors may include inertial sensors, cameras, radars, and light gates. As an illustrative example, a video camera may track motion of a pitched baseball, and an inertial sensor may track motion of a bat; the system may use the combined data to analyze the effectiveness of the swing in hitting the pitch. The system may also use sensor data to automatically select or generate tags for an event; tags may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags.

A system that analyzes data from multiple sensors, potentially of different types, that track motions of players, equipment, and projectiles such as balls. Data from different sensors is combined to generate integrated metrics for events and activities. Illustrative sensors may include inertial sensors, cameras, radars, and light gates. As an illustrative example, a video camera may track motion of a pitched baseball, and an inertial sensor may track motion of a bat; the system may use the combined data to analyze the effectiveness of the swing in hitting the pitch. The system may also use sensor data to automatically select or generate tags for an event; tags may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags.

Various implementations described herein are directed to a non-transitory computer readable medium having stored thereon computer-executable instructions which, when executed by a computer, may cause the computer to receive data recorded by a wearable device during a fishing trip. The computer may receive location data that corresponds to the fishing trip. The computer may use the data recorded by the wearable device to determine a time period for a fishing activity during the fishing trip. The computer may use the location data to determine locations corresponding to the time period.

Various implementations described herein are directed to a non-transitory computer readable medium having stored thereon computer-executable instructions which, when executed by a computer, may cause the computer to receive data recorded by a wearable device during a fishing trip. The computer may receive location data that corresponds to the fishing trip. The computer may use the data recorded by the wearable device to determine a time period for a fishing activity during the fishing trip. The computer may use the location data to determine locations corresponding to the time period.

Various implementations described herein are directed to a non-transitory computer readable medium having stored thereon computer-executable instructions which, when executed by a computer, may cause the computer to automatically receive motion capture data recorded by one or more cameras. The computer may analyze the motion capture data to detect a cast, catch, or bite. The computer may store a record of the cast, catch, or bite.

Various implementations described herein are directed to a non-transitory computer readable medium having stored thereon computer-executable instructions which, when executed by a computer, may cause the computer to automatically receive motion capture data recorded by one or more cameras. The computer may analyze the motion capture data to detect a cast, catch, or bite. The computer may store a record of the cast, catch, or bite.

A non-transitory computer-readable medium having stored thereon computer-executable instructions which, when executed by a computer, cause the computer to receive a first notification that a first cast has been made. The computer-executable instructions may further include instructions, which cause the computer to receive data regarding a video input. The computer-executable instructions may further include instructions, which cause the computer to receive a second notification that a second cast has been made. The computer-executable instructions may further include instructions, which cause the computer to delete a portion of the data regarding the video input that is associated with the first cast in response to receiving the second notification.