Cyril Cecchinel

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The Internet of Things (IoT) relies on physical objects interconnected between each others, creating a mesh of devices producing information. In this context, sensors are surrounding our environment (e.g., cars, buildings, smartphones) and continuously collect data about our living environment. Thus, the IoT is a prototypical example of Big Data. The(More)
Sensors networks are the backbone of large sensing infrastructures such as Smart Cities or Smart Buildings. Classical approaches suffer from several limitations hampering developers’ work (e.g., lack of sensor sharing, lack of dynamicity in data collection policies, need to dig inside big data sets, absence of reuse between implementation platforms). This(More)
Sensor networks are classically used in the Internet of Things to collect data, typically supporting Smart Cities or Smart Homes use cases. However, a deep knowledge of these networks is needed to properly develop applications over the deployed systems. This leads to a target mismatch: developers know how to exploit the collected data to develop large-scale(More)
Smart buildings and smart cities rely on interconnected sensor networks that collect data about their environment to support various applications. Developing and deploying the data collection architectures of these systems is a challenging problem. The specificities of the sensor platforms compel software engineers to work at a low level. This makes this(More)
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