19 June 2016
30 June 2016
15 July 2016
20 July 2016
10 October 2016
Data science is an interdisciplinary field that involves techniques to acquire, store, analyze, manage and publish data. For example, data can be analyzed using machine learning, data analysis and statistics, optimizing processes and maximizing their power in larger scenarios.
In the Internet of Things (IoT), smartphones and household appliances can easily become sensor nodes and compose sensor networks, measuring environmental parameters and generating user interaction data. As sensor networks are mainly data-oriented networks, i.e., sensed data is their most valuable asset and the reason for the operation of the whole network, data science techniques have been adopted to improve the IoT in terms of data throughput, self-optimization and self-management. In fact, incorporating the lifecycle proposed by the data scientists will impact the future of the IoT, allowing researchers to reproduce scenarios, and optimize the acquisition, analysis and visualization of the data acquired by IoT devices.
This workshop will address techniques used for data management planning into IoT scenarios in order to optimize data acquisition, management and later discovery.
The 13th IEEE International Conference on Mobile Ad hoc and Sensor Systems (IEEE MASS 2016) will be held in Brasilia, Brazil, October 10-13, 2016.
Wireless ad hoc communication has applications in a variety of environments, such as conferences, hospitals, battlefields, and disaster-recovery/rescue operations, and is also being actively investigated as an alternative paradigm for Internet connectivity in both urban and rural areas. Wireless sensor and actuator networks are also being deployed for enhancing industrial control processes and supply-chains, and for various forms of environmental monitoring. IEEE MASS 2016 aims at addressing advances in research on multihop ad hoc and sensor networks, covering topics ranging from technology issues to applications and test-bed development.