Autonomous vehicles (AVs) generate a massive amount of multi-modal data that once collected and processed through Machine Learning algorithms, enable AI-based services at the Edge. In fact, not all these data contain valuable, and informative content but only a subset of the relative attributes should be exploited at the Edge. Therefore, enabling AVs to locally extract such a subset is of utmost importance to limit computation and communication workloads. Achieving a consistent subset of data in a distributed manner imposes the AVs to cooperate in finding an agreement on what attributes should be sent to the Edge. In this work, we address such a problem by proposing a federated feature selection algorithm where all the AVs collaborate to filter out, iteratively, the redundant or irrelevant attributes in a distributed manner, without any exchange of raw data. This solution builds on two components: a Mutual-Information-based feature selection algorithm run by the AVs and a novel aggregation function based on the Bayes theorem executed on the Edge. Our federated feature selection algorithm provably converges to a solution in a finite number of steps. Such an algorithm has been tested on two reference datasets: MAV with images and inertial measurements of a monitored vehicle, WESAD with a collection of samples from biophysical sensors to monitor a relative passenger. The numerical results show that the fleet finds a consensus with both the datasets on the minimum achievable subset of features, i.e., 24 out of 2166 (99\%) in MAV and 4 out of 8 (50\%) in WESAD, preserving the informative content of data.
翻译:自动飞行器产生大量多模式数据,一旦通过机器学习算法收集和处理后,就能在边缘进行基于AI的服务。事实上,并非所有这些数据都包含有价值的信息内容,而且只有一部分相对属性,应该在边缘加以利用。因此,使自动飞行器在当地提取这样一个子集对于限制计算和通信工作量至关重要。 以分布方式取得一致的一组数据,使自动飞行器在寻找关于哪些属性应发送到Edge的协议时必须进行合作。在这项工作中,我们提出一个联合特征选择算法来解决这样一个问题,即所有AV都以分散的方式合作筛选、迭代、冗余或无关的属性,而无需交换任何原始数据。这一计算法基于两个组成部分:由AVs运行的基于互通信息的特性选择算法和基于在Edge上执行的Bayes orem的新型集成功能。 我们的节流特性选择算算算法在有限的几个步骤中汇集了这样一个问题。 所有AVS 以可实现的可实现性、 IMAS 4 和 IMA 的可实现的可实现性、 可实现性、 可实现性、可实现性、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可实现的、可及、可实现的、可实现的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、可及的、