Investigating IoT Middleware Platforms for Smart Application Development

With the growing number of Internet of Things (IoT) devices, the data generated through these devices is also increasing. By 2030, it is been predicted that the number of IoT devices will exceed the number of human beings on earth. This gives rise to the requirement of middleware platform that can manage IoT devices, intelligently store and process gigantic data generated for building smart applications such as Smart Cities, Smart Healthcare, Smart Industry, and others. At present, market is overwhelming with the number of IoT middleware platforms with specific features. This raises one of the most serious and least discussed challenge for application developer to choose suitable platform for their application development. Across the literature, very little attempt is done in classifying or comparing IoT middleware platforms for the applications. This paper categorizes IoT platforms into four categories namely-publicly traded, open source, developer friendly and end-to-end connectivity. Some of the popular middleware platforms in each category are investigated based on general IoT architecture. Comparison of IoT middleware platforms in each category, based on basic, sensing, communication and application development features is presented. This study can be useful for IoT application developers to select the most appropriate platform according to their application requirement

A Feedback-Based Adaptive Service-Oriented Paradigm for the Internet of Things

© Springer International Publishing AG, part of Springer Nature 2018. With integrating physical devices into digital world, Internet of Things (IoT) have presented tremendous potential in various different application domains such as smart cities, intelligent transportation, smart home, healthcare and industrial automation. However, current IoT solutions and usage scenarios are still very limited because of the difficulty in sensing the context in continuously changing environments and adaptation to the changes accordingly. The complex dynamic interactions between system components and physical environments are a bit challenging especially when there are other concerns such as scalability and heterogeneity. To solve this problem, a novel adaptive service-oriented paradigm is proposed to support IoT from a low-level viewpoint. The paradigm can overcome some disadvantages of REST (Representational State Transfer) architecture style in the IoT. Two classical examples are illustrated using the proposed paradigm by adding an extra constraint based on REST to improve system states verification and enhance the functionality in modelling physical processes

Data provenance to audit compliance with privacy policy in the Internet of Things

Managing privacy in the IoT presents a significant challenge. We make the case that information obtained by auditing the flows of data can assist in demonstrating that the systems handling personal data satisfy regulatory and user requirements. Thus, components handling personal data should be audited to demonstrate that their actions comply with all such policies and requirements. A valuable side-effect of this approach is that such an auditing process will highlight areas where technical enforcement has been incompletely or incorrectly specified. There is a clear role for technical assistance in aligning privacy policy enforcement mechanisms with data protection regulations. The first step necessary in producing technology to accomplish this alignment is to gather evidence of data flows. We describe our work producing, representing and querying audit data and discuss outstanding challenges.Engineering and Applied Science

Contribution a l'etude theorique et experimentale et a la modelisation d'une pompe a chaleur en cascade a tres haute temperature

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

A model-driven engineering approach for the service integration of IoT systems

With the development of IoT devices and web services, the objects of the real world are more interconnected, which allows applications to extend their characteristics in different fields, including industrial or home environments, among other possible examples such as health, trade, transport, or agriculture. However, this development highlights the challenge of interoperability, because devices are heterogeneous and use different communication protocols and different data formats. For this reason, we propose a model for point-to-point integration in three-layer IoT applications: (a) hardware, which corresponds to the physical objects (controller, sensor and actuator), (b) communication, which is the bridge that allows the exchange of data between a MQTT queue and REST web services, and (c) integration, which establishes a sequence of transactions to coordinate the components of the system. For this purpose, a metamodel, a graphic editor and a code generator have been developed that allow the developer to design IoT systems formed by heterogeneous components without having in-depth knowledge of every hardware and software platform. In order to validate our proposal, a smart home scenario has been developed, with a series of sensors and actuators that combined show a complex behavior