This research challenged the restructuring conceptual framework of compact city at shrinking regional town in Japan looking ahead to after corona. In general, concept of compact city is based on the premise the growth of population. However, we proposed to apply the conceptual framework of "intensified plus leavy land use planning" to regional shrinking city. This concept is basically applied the concept of urban stock to be updated for new use. We also make a proposal such as the greenroad, intensive previously-used land, and promoting temporary immigration from urban to provincial town; jobcation and multihabitat could be an example of a temporary immigration style.
Systems for estimating human motion using acceleration sensors present the following two problems: 1) advanced analysis and processing of sensor data are difficult because of resource limitations of sensor nodes; and 2) such analyses and processes burden the network because numerous sensor data are sent to the network. The authors’ proposed method described herein for sensor data analysis and processing uses a host computer located near sensor nodes (neighborhood host). This method is intended to achieve a good balance between reduction of the network load and advanced sensor data analysis and processing. Moreover, this method incorporates reduction of the load to sensor nodes. To evaluate their method, the authors implement two prototype systems that use different machine learning methods. The authors conduct some experiments using these prototype systems. The experimentally obtained results demonstrate that the proposed method can resolve two problems.
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