The transport industry will undergo major changes, as a result of which both the enterprises themselves and their customers will be able to get benefits. And here technology is the main key to convenience and comfort. The following are a few examples successfully used in the transportation industry by our team:
- Real-time data applications such as GPS monitoring systems
- Augmented Reality (smart glasses and cards)
- Beacons (signal beacons connected to the car and transmitting the signal to the smartphone. They can predict traffic or be installed on road signs, sending notifications about this)
- The Internet of things and smart transport (For example, smart sensors integrated into the transport that transmit information about hijacking attempts or status)
Our research group proceeds a large amount of multi-modal data from electronic health records, cameras, and medical devices to develop AI-based systems that can assist clinicians and staff in their medical routines.
To ensure privacy and security while training our ML models, we utilize federated learning alongside with series of data protection techniques in federated learning pipeline as data aggregation, perturbation, secure multi-party computations, homomorphic encryption, etc.
We do believe that data fused and processed in a proper way combined with medical knowledge and experience and enriched with ad-hoc models, techniques, and analytic software tools are able to boost healthcare analytics, helping doctors, nurses, and medical staff provide the best decisions to possible care and treatment to patients.