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Titlebook: Data Science and Internet of Things; Research and Applica Giancarlo Fortino,Antonio Liotta,Alessandro Longhe Book 2021 Springer Nature Swit

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21#
發(fā)表于 2025-3-25 06:48:44 | 只看該作者
Collaborative Solutions for Unmanned Aerial Vehicles,f the vertical takeoff and landing (VTOL) type are still facing, detailing their key application areas. Afterward, we discuss some solutions where wireless communications between UAVs enable achieving advanced collaborative solutions such as flight coordination and collision avoidance.
22#
發(fā)表于 2025-3-25 08:26:20 | 只看該作者
Book 2021ort IoT. The authors show how data science methodologies, techniques and tools, can translate data into information, enabling the effectiveness and usefulness of new services offered by IoT stakeholders. The authors posit that if IoT is indeed the infrastructure of the future, data structure is the
23#
發(fā)表于 2025-3-25 14:01:12 | 只看該作者
IoT Aided Smart Home Architecture for Anomaly Detection,malies from the usual, everyday activities. An experimental study, as proof of concept for the fire emergence case, is run by using LSTM neural network architecture. One of the positive features of the proposed methodology is that the faulty readings and false positive alarms on specific parameters
24#
發(fā)表于 2025-3-25 19:30:56 | 只看該作者
Evolutionary Dynamics and Multiplexity for Mobile Edge Computing in a Healthcare Scenario,evaluate the impact of evolutionary dynamics of cooperation of mobile edge computing nodes in the system. Our findings show how the evolutionary dynamics of mobile edge computing nodes allow decreasing the blocking probability, with the increasing of cooperators in the considered scenario.
25#
發(fā)表于 2025-3-25 20:15:08 | 只看該作者
Graph and Network Theory for the Analysis of Criminal Networks, popular artificial network models: Watts-Strogats, Erd?s-Rényi, and Barabási-Albert, with some topology variations. This chapter will be a valuable tool for researchers who wish to employ social network analysis within their own area of interest.
26#
發(fā)表于 2025-3-26 04:01:16 | 只看該作者
A Data Mining Approach for Indoor Navigation Systems in IoT Scenarios,d distance and elapsed time. It also improved routing by decreasing the number of turns and encounters with obstacles. Thus, the proposed method provides better solution as an intelligent indoor navigation.
27#
發(fā)表于 2025-3-26 04:43:01 | 只看該作者
Other Approaches to Coping with Hardness?malies from the usual, everyday activities. An experimental study, as proof of concept for the fire emergence case, is run by using LSTM neural network architecture. One of the positive features of the proposed methodology is that the faulty readings and false positive alarms on specific parameters
28#
發(fā)表于 2025-3-26 09:57:26 | 只看該作者
29#
發(fā)表于 2025-3-26 13:04:52 | 只看該作者
https://doi.org/10.1007/978-3-642-25749-0 popular artificial network models: Watts-Strogats, Erd?s-Rényi, and Barabási-Albert, with some topology variations. This chapter will be a valuable tool for researchers who wish to employ social network analysis within their own area of interest.
30#
發(fā)表于 2025-3-26 19:54:27 | 只看該作者
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