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In the recent era of the Internet of Things, the dominant role of sensors and the Internet provides a solution to a wide variety of real-life problems. Such applications include smart city, smart healthcare systems, smart building, smart transport and smart environment. However, the real-time IoT sensor data include several challenges, such as a deluge of unclean sensor data and a high resource-consumption cost. As such, this paper addresses how to process IoT sensor data, fusion with other data sources, and analyses to produce knowledgeable insight into hidden data patterns for rapid decision-making. This paper addresses the data processing techniques such as data denoising, data outlier detection, missing data imputation and data aggregation. Further, it elaborates on the necessity of data fusion and various data fusion methods such as direct fusion, associated feature extraction, and identity declaration data fusion. This paper also aims to address data analysis integration with emerging technologies, such as cloud computing, fog computing and edge computing, towards various challenges in IoT sensor network and sensor data analysis. In summary, this paper is the first of its kind to present a complete overview of IoT sensor data processing, fusion and analysis techniques.

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Deploying drones over the Cloud is an emerging research area motivated by the emergence of Cloud Robotics and the Internet-of-Drones (IoD) paradigms. This paper contributes to IoD and to the deployment of drones over the cloud. It presents, Dronemap Planner, an innovative service-oriented cloud based drone management system that provides access to drones through web services (SOAP and REST), schedule missions and promotes collaboration between drones. A modular cloud proxy server was developed; it acts as a moderator between drones and users. Communication between drones, users and the Dronemap Planner cloud is provided through the MAVLink protocol, which is supported by commodity drones. To demonstrate the effective-ness of Dronemap Planner, we implemented and validated it using simulated and real MAVLink-enabled drones, and deployed it on a public cloud server. Experimental results show that Dronemap Planner is efficient in virtualizing the access to drones over the Internet, and provides developers with appropriate APIs to easily program drones 19 applications.A Service-Oriented Cloud-Based Management System for the Internet-of-Drones Abstract-Deploying drones over the Cloud is an emerging research area motivated by the emergence of Cloud Robotics and the Internet-of-Drones (IoD) paradigms. This paper contributes to IoD and to the deployment of drones over the cloud. It presents, Dronemap Planner, an innovative service-oriented cloud based drone management system that provides access to drones through web services (SOAP and REST), schedule missions and promotes collaboration between drones. A modular cloud proxy server was developed; it acts as a moderator between drones and users. Communication between drones, users and the Dronemap Planner cloud is provided through the MAVLink protocol, which is supported by commodity drones. To demonstrate the effectiveness of Dronemap Planner, we implemented and validated it using simulated and real MAVLink-enabled drones, and deployed it on a public cloud server. Experimental results show that Dronemap Planner is efficient in virtualizing the access to drones over the Internet, and provides developers with appropriate APIs to easily program drones' applications.

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