Towards smart homes using low level sensory data.

Ubiquitous Life Care (u-Life care) is receiving attention because it provides high quality and low cost care services. To provide spontaneous and robust healthcare services, knowledge of a patient's real-time daily life activities is required. Context information with real-time daily life activities can help to provide better services and to improve healthcare delivery. The performance and accuracy of existing life care systems is not reliable, even with a limited number of services. This paper presents a Human Activity Recognition Engine (HARE) that monitors human health as well as activities using heterogeneous sensor technology and processes these activities intelligently on a Cloud platform for providing improved care at low cost. We focus on activity recognition using video-based, wearable sensor-based, and location-based activity recognition engines and then use intelligent processing to analyze the context of the activities performed. The experimental results of all the components showed good accuracy against existing techniques. The system is deployed on Cloud for Alzheimer's disease patients (as a case study) with four activity recognition engines to identify low level activity from the raw data captured by sensors. These are then manipulated using ontology to infer higher level activities and make decisions about a patient's activity using patient profile information and customized rules.

A New Approach for the Fabrication of Tetragonal BaTiO3 Nanoparticles.

For the first time, the BaTiO3 nano-sized particles were obtained through solid-state reaction by employing the titanium oxide nanoparticle. Meanwhile, by using TiO2 with micro-sized particles, the synthesized BaTiO3 shows the micro-sized. The XRD pattern confirms that both BaTiO3 nano-sized and micro-sized particles display the tetragonal structure. Both SEM and TEM analysis revealed that the size of the nano-sized material is in the range of 30-50 nm; in the meantime, the microsized material shows a size of 500 nm. The Eg of both BaTiO3 micro-sized and nano-sized were calculated by using the Kubelka-Munk function. The shifted bandgap of BaTiO3 nano-sized particle is nearly 0.24 eV larger than that of BaTiO3 miro-sized particle due to the particle size effect. The P-E measurement of n-BaTiO3 proved that the obtained BaTiO3 nano-sized is ferroelectric material. The result may provide a new route for the fabrication of barium titanate nanoparticle with ferroelectric properties.