In the last few years, many health monitoring systems have been designed to fullfil the needs of a large range of scenarios. Although many of those systems provide good ad hoc solutions, most of them lack of mechanisms that allow them to be easily reused. This paper is focused on describing an open platform, the micro Web of Things Open Platform (µWoTOP), which has been conceived to improve the connectivity and reusability of context data to deliver different kinds of health, wellness and ambient home care services. µWoTOP is based on a resource-oriented architecture which may be embedded in mobile and resource constrained devices enabling access to biometric, ambient or activity sensors and actuator resources through uniform interfaces defined according to a RESTful fashion. Additionally, µWoTOP manages two communication modes which allow delivering user context information according to different methods, depending on the requirements of the consumer application. It also generates alert messages based on standards related to health care and risk management, such as the Common Alerting Protocol, in order to make its outputs compatible with existing systems.

Advances in electronics nowadays facilitate the design of smart spaces based on physical mash-ups of sensor and actuator devices. At the same time, software paradigms such as Internet of Things (IoT) and Web of Things (WoT) are motivating the creation of technology to support the development and deployment of web-enabled embedded sensor and actuator devices with two major objectives: (i) to integrate sensing and actuating functionalities into everyday objects, and (ii) to easily allow a diversity of devices to plug into the Internet. Currently, developers who are applying this Internet-oriented approach need to have solid understanding about specific platforms and web technologies. In order to alleviate this development process, this research proposes a Resource-Oriented and Ontology-Driven Development (ROOD) methodology based on the Model Driven Architecture (MDA). This methodology aims at enabling the development of smart spaces through a set of modeling tools and semantic technologies that support the definition of the smart space and the automatic generation of code at hardware level. ROOD feasibility is demonstrated by building an adaptive health monitoring service for a Smart Gym.