Yuto Lim

TL;DR: This study proposes a novel framework to not only recognize human activity but also predict it and shows that the hardware cost of the framework is sufficiently low to popularize the framework and can realize good performance in both activity recognition and prediction with high scalability.

TL;DR: A survey of the latest research on intelligent data processing technology applied in agriculture, particularly in rice production, can be found in this paper, where the authors describe the data captured and elaborate role of machine learning algorithms in paddy rice smart agriculture.

TL;DR: It is claimed that personal assistive robots should likewise be culturally competent, aware of general cultural characteristics and of the different forms they take in different individuals, and sensitive to cultural differences while perceiving, reasoning, and acting.

TL;DR: The state-of-the-art of PoR is examined and the issues and challenges as a result of employing PoR specifically and cloud storage generally are described and some possible countermeasures to address the identified issues are suggested.

TL;DR: A cyber–physical human centric system (CPHCS) framework is proposed to take advantage of individual human thermal comfort to improve the human’s thermal comfort level while optimizing the energy consumption at the same time.