Autonomous sensors that monitor and control physical or environmental conditions.
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Visual identification of structural flaws is quite valuable not only to predict an imminent collapse of a bridge, but also to determine effective precautionary measures and repairs.
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This project aims to investigate energy and delay sensitive sensing, communication, decision-making and control in the context of cyber physical systems. We particularly focus on systems where sensors with varying accuracy observe heterogeneous source signals that must be processed and communicated and used for inference and decision-making purposes.
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A challenge for assisting young developmentally-delayed children in learning to walk is to (1) stabilize medio-lateral body sway while promoting opportunities for exploratory behavior, and (2) develop gait that exploits exchange of potential and kinetic energy. To meet the challenge, we have built a modular multi-robot CPS: a scaffold that applies forces at the pelvis via cables to modulate and stabilize center of mass behavior, and a wearable robot that applies assistive torques at the hip.
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The recent increase in the variety and usage of wearable sensing systems allows for the continuous monitoring of health and wellness of users. The output of these systems enable individuals to make changes to their personal routines in order to minimize exposures to pollutants and maintain healthy levels of exercise. Furthermore, medical practitioners are using these systems to monitor proper activity levels for rehabilitation purposes and to monitor threatening conditions such as heart arrhythmias.
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Our proposal's main objective is to realize cyber-physical platform and principles for (i) interrogating global modalities of intracellular transport with causative factors isolated at the single-molecule scale and (ii) realizing efficient and robust infrastructure for transporting micron/molecular scale cargo using distributed strategies We are realizing in-vitro, a transport network with roadways formed by microtubules where motorproteins, kinesin and dynein, will form vehicles ferrying cargo.
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The objective of this project is to improve the performance of autonomous systems in dynamic environments by integrating perception, planning paradigms, learning, and databases. For the next generation of autonomous systems to be truly effective in terms of tangible performance improvements (e.g., long-term operations, complex and rapidly changing environments), a new level of intelligence must be attained.
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The goal of this project is to demonstrate that new cyber-physical architectures will enable closed-loop sensor networks to be shared among multiple applications and to dynamically allocate sensing and computing resources necessary to analyze sensor data and perform sensor actuation. The sharing of sensor network infrastructures will make the provision of data (e.g., weather information) more cost efficient and will create cyber infrastructures, which will result in a dramatic increase in the number of sensor networks available for use.
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The SONYC project is a smart cities initiative focused on developing a cyber-physical system (CPS) for the monitoring, analysis and mitigation of urban noise pollution. Noise pollution is one of the topmost quality of life issues for urban residents in the U.S. with proven effects on health, education, the economy, and the environment.
