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Goal: small smart sensors Motivation: Current sensors are "static", detecting just one thing, such as light, sound, or touch, because of which in complex systems such as vehicles or homes many sensors are typically required. A "smart" sensor which could dynamically adapt itself (to detect different signals) could replace multiple static sensors, leading to less space taken, less cost, less work for installations, a greater ability to operate when changes occur, and possibly even easier repairs (self-healing). Alternatively, an ensemble of dynamic sensors could acquire more information than the same number of static sensors. Furthermore, if such sensors can be made small, various benefits would emerge: e.g., making arbitrary surfaces embedded with sensors for robots such as intelligent skin, and interesting tasks at the micro scale could potentially be facilitated, such as monitoring cells inside of a person. Challenges: It is unknown how a sensor could be automatically changed into a different kind of sensor, a good strategy for changing a sensor or an ensemble of sensors, and how to achieve this at a small scale. Approach: The student will -Design transitions between some typical sensors -Design algorithms for calculating information/interestingness for each modality (possibly using change point detection) and for strategically allocating roles (like particles in a particle filter). -Design a strategy for the micro scale -Implement a macro-scale proof-of-concept, which can be switched manually or algorithmically, and a smaller proof-of-concept (mini, or micro; nano would be cool but would probably not be possible) -Evaluate -Thus, students will develop both software, and hardware/electronics Expected result: some ideas (new knowledge) of how to adapt different sensors, at different scales. Thesis, prototypes, video, hopefully a paper, possibly other such as code
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