GIS Design: A review of current issues in interoperability

The evolution of Geographic Information Systems (GIS) has witnessed an important step towards achieving interoperability through the communication, exchange, cooperation and sharing of resources between systems. The main developments in interoperability include the use of standards for transfer and exchange of geographical information, the integration of different data types up to the development of comprehensive interoperability models. This article aims to review the main advances in interoperability of GIS and provide a basis to identify the future research issues in this field. It first considers the various points of view from which interoperability can be defined and then examines the concept of interoperability itself. An overview is provided on how interoperability can be modelled by discussing the main aspects that directly have an effect on how interoperability levels have been created according to different contexts and purposes of use. It also points out the significant advances in terms of measures that can determine the ability of a GIS to interoperate with other systems, predict the resources needed for successful interoperation, and discover techniques useful to achieving interoperability. We conclude with some suggestions where the research will go nex

A mobility constraint model to infer sensor behaviour in forest fire risk monitoring

Wireless sensor networks (WSNs) play an important role in forest fire risk monitoring. Various applications are in operation. However, the use of mobile sensors in forest risk monitoring remains largely unexplored. Our research contributes to fill this gap by designing a model which abstracts mobility constraints within different types of contexts for the inference of mobile sensor behaviour. This behaviour is focused on achieving a suitable spatial coverage of the WSN when monitoring forest fire risk. The proposed mobility constraint model makes use of a Bayesian network approach and consists of three components: (1) a context typology describing different contexts in which a WSN monitors a dynamic phenomenon; (2) a context graph encoding probabilistic dependencies among variables of interest; and (3) contextual rules encoding expert knowledge and application requirements needed for the inference of sensor behaviour. As an illustration, the model is used to simulate the behaviour of a mobile WSN to obtain a suitable spatial coverage in low and high fire risk scenarios. It is shown that the implemented Bayesian network within the mobility constraint model can successfully infer behaviour such as sleeping sensors, moving sensors, or deploying more sensors to enhance spatial coverage. Furthermore, the mobility constraint model contributes towards mobile sensing in which the mobile sensor behaviour is driven by constraints on the state of the phenomenon and the sensing syste