This study proposes a system for estimating individual emotions based on collected indoor environment data for human participants. At the first step, we develop wireless sensor nodes, which collect indoor environment data regarding human perception, for monitoring working environments. The developed system collects indoor environment data obtained from the developed sensor nodes and the emotions data obtained from pulse and skin temperatures as big data. Then, the proposed system estimates individual emotions from collected indoor environment data. This study also investigates whether sensory data are effective for estimating individual emotions. Indoor environmental data obtained by developed sensors and emotions data obtained from vital data were logged over a period of 60 days. Emotions were estimated from indoor environmental data by machine learning method. The experimental results show that the proposed system achieves about 80% or more estimation correspondence by using multiple types of sensors, thereby demonstrating the effectiveness of the proposed system. Our obtained result that emotions can be determined with high accuracy from environmental data is a useful finding for future research approaches.

This paper investigates an indoor location estimation system based on UHF band RFID. Tags, separated by 50 cm, are attached to the ceiling and an RFID reader is attached to the person of interest. The location of the person is estimated using the tags' coordinate which are read by the RFID reader. Three simple location estimation algorithms are proposed, and their estimation accuracy is evaluated by an experiment. This paper also presents a ray trace simulation; tag allocation, RFID reader parameters, and location estimation algorithms are evaluated by simulation to minimize the estimation error.

The purpose of this paper is to analyze the maximum throughput when using RTS/CTS (Request To Send/Clear To Send) in IEEE 802.11 Distributed Coordination Function (DCF) multi-hop networks with a novel approach. Wireless multi-hop networks, in which nodes communicate with each other and convey packets via intermediate nodes without centralized control, have gained increasing attention because of the extension of the wireless communication range associated with such networks. In wireless multi-hop networks, the IEEE 802.11 DCF based on the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) has been commonly used as a Medium Access Control (MAC) protocol. IEEE 802.11 DCF is specifically designed for single-hop wireless LANs, which makes quantitative analyses of the contention behaviors occurring at nodes in typical network topologies important. Although several quantitative throughput analyses for wireless multi-hop networks have been reported, few analyses have examined the use of RTS/CTS in IEEE 802.11 DCF multi-hop networks. While RTS/CTS is effective for avoiding packet collisions caused by hidden terminals, an overhead problem occurs due to the increase in the number of RTS/CTS control packets. As the number of RTS/CTS control packets increases, the collisions between RTS/CTS control packets occur more frequently. The analysis of networks that use RTS/CTS has been considered difficult because of the complex behaviors of RTS/CTS. The present paper introduces a novel approach to the analysis of throughput for networks that use RTS/CTS by considering one-way flow in string multi-hop networks. The end-to-end network maximum throughput is obtained by analyzing the maximum throughput of bottleneck nodes. This analysis provides the transmission failure probability considering not only RTS-RTS collisions but also the influence of the Network Allocation Vector (NAV). A simulation is carried out, and a comparison of the analytical and simulated results validates the proposed analytical expressions.