Smart farming envisages the harnessing of Information and Communication Technologies as an enabler of more efficient, productive, and profitable farming enterprises. Such technologies do not suffice on their own; rather they must be judiciously combined to deliver meaningful information in near real-time. Decision-support tools incorporating models of disparate farming activities, either on their own or in combination with other models, offer one popular approach; exemplars include GPFARM, APSIM, GRAZPLAN amongst many others. Such models tend to be generic in nature and their adoption by individual farmers is minimal. Smart technologies offer an opportunity to remedy this situation; farm-specific models that can reflect near real-time events become tractable using such technologies. Research on the development, and application of farm-specific models is at a very early stage. This paper thus presents an overview of models within the farming enterprise; it then reviews the state-of the art in smart technologies that promise to enable a new generation of enterprise-specific models that will underpin future smart farming enterprises

The idea of ambient intelligence implies an intrinsic link between individuals and their environment, enabling individuals to access and interact with computing artifacts in ways that are intuitive and do not disrupt everyday activities. Given the many different environments encountered as part of everyday life—within the home (1) as well as beyond it—enabling such interaction is a formidable technological challenge. The reward may be an environment that is safer, uses less energy, and responds to the needs of all individuals (see the figure). Recent advances in embedded systems, robotics, and sensor technology suggest that ambient intelligence may indeed be realized, particularly if crucial privacy and security concerns are addressed.

Reducing energy consumption within buildings has been an active area of research in the past decade; more recently, there has been an increased influx of activity, motivated by a variety of issues including legislative, tax-related, as well as an increased awareness of energy-related issues. Energy usage both in commercial and residential buildings represents a significant portion of overall energy consumption; however, much of this may be categorized as waste, that is, energy usage that does not fulfil a definite purpose. In the past decade, the viability of Wireless Sensor Network (WSN) technologies has been demonstrated, leading to increased possibilities for novel services for building energy management. This development has resulted in numerous approaches being proposed for harnessing WSNs for energy management and conservation. This article surveys the state-of-the-art in building energy management systems. A generic architecture is proposed after which a detailed taxonomy of existing documented systems is presented. Gaps in the literature are highlighted and directions for future research identified.