Research overview
Intelligent cameras such as video doorbells and CCTV are abundant today, yet only used for a single-purpose, privacy-invasive and bandwidth-heavy streaming.
Nokia Bell Labs has developed a software solution that transforms intelligent cameras with automated machine learning operations (MLOps), enabling them to provide a range of services, including traffic flow, pedestrian analysis, asset tracking, or even facial recognition. With robust security controls and privacy-preserving query serving, the data is kept safe and anonymized.
By running multiple machine learning (ML) models that can be updated over the air, these cameras become agile, multi-functional, and upgradable devices as new algorithms enable different capabilities to be added on demand.
APA style publications
- Chulhong Min, Akhil Mathur, Alessandro Montanari, and Fahim Kawsar, “SensiX: A System for Best-effort Inference of Machine Learning Models in Multi-device Environments,” in IEEE Transactions on Mobile Computing, 2022doi: 10.1109/TMC.2022.3173914. (Link)
- Utku Günay Acer, Marc van den Broeck, Chulhong Min, Mallesham Dasari, and Fahim Kawsar. 2022. “The City as a Personal Assistant: Turning Urban Landmarks into Conversational Agents for Serving Hyper Local Information,” in Proc. ACM Interactive, Mobile, Wearable and Ubiquitous Technologies. 6, 2, Article 40 (July 2022), 31 pages. (Link)
- Alessandro Montanari, Manuja Sharma, Dainius Jenkus, Mohammed Alloulah, Lorena Qendro, and Fahim Kawsar. 2020. ePerceptive: energy reactive embedded intelligence for batteryless sensors. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems (SenSys '20). Association for Computing Machinery, New York, NY, USA, 382–394. (Link)
