<span>This article reports on an m-learning research agenda instituted at our university in order to explore how mobile technology can enhance active, experiential learning. Details of the implementation and results of four areas of m-learning are presented: mobile supported fieldwork, fostering interactivity in large lectures with mobile technology, using mobile devices to learn about mobile technology and, finally, podcasting. These directions are informed by a concern for achieving m-learning practices consistent with sound educational theory and the needs of the contemporary, technologically aware student body. All four implementations have been successfully embedded in mainstream subjects on a continuing basis. Therefore they represent a departure from the project based approach of much m-learning reported in the literature. This outcome was achieved through a focus on the economic sustainability and feasibility of each case. An evaluation focusing on how well each case assisted students' learning found that, with the exception of lecture podcasting, all supported high quality experiential learning.</span>

An increasing aged population worldwide puts our medical capabilities to the test. Research and commercial groups are investigating novel ways to care for the aged and chronically ill both in their own homes and in care facilities. This paper describes a prototype we have developed for remote healthcare monitoring. This personalized smart homecare system uses smart phones, wireless sensors, web servers and IP webcams. To illustrate the functionality of the prototype we describe a series of typical tele-health monitoring scenarios.

The rapid scientific and technological merging between Internet of Things (IoT), cloud computing and wireless body area networks (WBANs) have significantly contributed to the advent of e-healthcare. Due to this the quality of medicinal care has also been improved. Specifically, patient-centric health care monitoring plays important role in e-healthcare facilities by providing important assistance in different areas, including medical data collection and aggregation, data transmission, data processing, data query, and so on. This paper proposed an architectural framework to describe complete monitoring life cycle and indicates the important service modules. More meticulous discussions are then devoted to data gathering at patient side, which definitely serves as essential basis in achieving efficient, vigorous and protected patient health monitoring. Different design challenges are also analyzed to develop a high quality and protected patient-centric monitoring systems along with their possible potential solutions.

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