The drones showcase demonstrates, how through interaction of real-time data and the Watson IoT platform e.g. city traffic can be better monitored and made safer.
IBM and DJI are working together to demonstrate the integration of drone data with Watson IoT Platform on a traffic monitoring scenario, one of many different applications for these technologies. Instead of receiving data and updates from ground personnel such as the police, stationary cameras, or helicopters, the use of drones can lower costs and improve data accuracy, which leads to increased efficiency and thus public safety.
The drones are remotely operated and will patrol a miniature city scape with busy streets and highways built inside a cage. The real-time data collected will be fed into IBMs visual recognition APIs, Watsons cognitive computing and the Bluemix cloud based analysis platform. The data will then be processed to discover traffic patterns and potential or actual issues, such as traffic congestions or accidents. The analysis results will be displayed in a dashboard format showing various traffic scenarios, including options for e.g. emergency response. In a continuous cycle, the systems will process new data as it comes in and the dashboards will be updated automatically.
In this application, the synergy of these technologies enables faster response times to traffic issues with the potential to save lives in the process.
With Olli, IBM presents the future of autonomous driving and passenger transportation.
Olli, built by Local Motors, is the first self-driving commuter bus using the cloud-based IBM Watson technology. The small bus can carry up to 12 passengers, does not need a driver, and is intended for inner-city commuting.
Olli will be using a special Watson for Automotive applications version with the following Watson APIs: Speech to Text, Natural Language Classifier, Entity Extraction, and Text to Speech. This improves the integration of vehicle and passenger by simplifying communication for passengers and making the ride more interesting, e.g. passengers can chat with Olli during their ride and receive recommendations for local restaurants or other interesting locations.
With the help of these applications, Olli is able to analyze the transportation data of 30+ sensors located on the vehicle in seconds, and thus react to exterior influences in street traffic. Olli keeps learning with every single new data point that Watson collects, which improves the service offered to passengers. Additional sensors can be integrated into the vehicle to adapt Olli to specific local environments.
CeBIT visitors will have the opportunity to personally meet Olli. A showcase with Olli at a bus stop will demonstrate, how Olli is used in public.