Las Vegas – At CES 2017, Alarm has announced plans to develop autonomous, video unmanned aerial vehicle applications that extend the functionality of smart home and business security systems.
The UAV will use Alarm’s new intelligence multi-sensor sensing and attributes, known as the Insight Engine, along with Qualcomm’s Snapdragon UAV platform to explore unexpected activity.
The UAV will be designed to autonomously navigate the properties and provide owners with high-resolution video.
The company’s new insights into engine learning capabilities, which have also been announced at CES, are machine learning algorithms that apply to growing dataset-generated device and sensor connectivity properties. By identifying complex activity patterns and detecting anomalies, the system can represent the user’s active response events.
Alarm intends to use these insights to intelligently deploy video UAV locations to find unexpected activities or when alarms are triggered. Strictly, the choice of privacy controls will enable the owners to share video feeds with the central monitoring station, emergency personnel.
“This is a very interesting UAV, applying Snapdragon processor in its core that is essentially flying a camera, and using other advanced features, Alarm is designed to provide a new way to provide security properties,” said Hugo swarthy “Qualcomm Snapdragon Flight Platform drives the boundaries of the UAV industry, resulting in many new forms of factors and use cases, and Alarm.com, a security expert in the commercial and residential security systems that integrates into the The next level of intelligence and cutting-edge solutions for unmanned aerial vehicles. ”
“Alarm has become a smart home and business security space,” said Daniel Kerzner, Chief Product Officer of Alarm. “By analyzing the data on the device on our platform, we have created unique features that make the performance safer, smarter and more efficient.” We are excited to develop similar applications with Qualcomm’s Snapdragon UAVs. Human-machine deployment systems will be designed to provide targeted video to respond to specific events in a single attribute – adding fixed-position cameras and enhancing active security for home and business perimeter. ”
Insight Engine’s new patented machine learning capabilities protect families and businesses by identifying patterns and insights in the growing dataset of generated device and sensor connectivity attributes.
By learning the unique activity patterns of any home or business, the insights engine can respond to unusual activity on behalf of the homeowners to take action through the extensive ecosystem of Alarm Link devices.
“Alarm has always aggregated sensor data to create a smart, active and context-aware experience in smart home,” Kerzner said. “The insights engine is an example of how we extend the next generation of intelligent home solutions with machine learning methods to define.”
Unexpected Activity Notification: The first application of the Insight Engine is a new category of IntelliSense notifications that alert families about potential security or security issues in their homes. If the insights engine determines that the homeowner should be alerted, send push notifications to all homeowners that have not had to create custom rules or notifications. E.g:
Early games: The front door of a home is frequently turned on and off early in the morning on weekdays as the work of home and school. On weekends, however, it is usually open later in the day. When the door opens on a Saturday morning, an unexpected event advises the homeowner that the children are exploring the front yard.
Dating Night: The front door of a home is usually locked at 7:30 pm on weekdays and 9 pm on weekends. At dinner, the owner receives a notice that the door is still locked at 9:15 am on Saturday and is aware that the nanny forgets to lock. Based on this information, they use their Alarm application to lock the door remotely.
Adaptive learning: The Alarm insight engine is continually adapted to changes based on a number of factors, including user input, activity patterns, and external factors.
Actionable notifications allow users to “train” smart homes to learn their preferences faster and adapt quickly to new schedules. The notification has simple feedback options that include the availability of each notification as yes or no, allowing the insights engine to quickly adapt based on minimal user input. The third option allows the user to “pause” the notification of feedback within 24 hours of a sudden but temporary arrangement to change the day of the sick.
Time-intelligent notification adjusts the sensitivity depending on the event that occurs. Open doors in the garage during the day, for example, may not trigger notifications immediately. However, after sunset, system security risks become more sensitive and are more likely to immediately alert the owner.
