Emerging precision agriculture techniques rely on the frequent collection of high-quality data which can be acquired efficiently by unmanned aerial systems (UAS). The main obstacle for wider adoption of this technology is related to UAS operational costs. The path forward requires a high degree of autonomy and integration of the UAS and other cyber physical systems on the farm into a common Farm Management System (FMS) to facilitate the use of big data and artificial intelligence (AI) techniques for decision support. Such a solution has been implemented in the EU project AFarCloud (Aggregated Farming in the Cloud). The regulation of UAS operations is another important factor that impacts the adoption rate of agricultural UAS. An analysis of the new European UAS regulations relevant for autonomous operation is included. Autonomous UAS operation through the AFarCloud FMS solution has been demonstrated at several test farms in multiple European countries. Novel applications have been developed, such as the retrieval of data from remote field sensors using UAS and in situ measurements using dedicated UAS payloads designed for physical contact with the environment. The main findings include that (1) autonomous UAS operation in the agricultural sector is feasible once the regulations allow this; (2) the UAS should be integrated with the FMS and include autonomous data processing and charging functionality to offer a practical solution; and (3) several applications beyond just asset monitoring are relevant for the UAS and will help to justify the cost of this equipment.

In this paper, we compare a method for selecting transmission antenna based on road curvature to a method based on periodically alternating between left and right hand side transmission antennas. Both methods aim to improve the success rate for communication between participants in a platoon of vehicles. Moreover, we propose the data age metric for online use as input to the algorithm controlling the inter-vehicle distance in platooning, e.g. to decide appropriate gap between the vehicles depending on the V2V communication quality. The methods have been evaluated through V2V communication measurements performed using heavy duty vehicles on public highway. We show that, when using the curvature-based method, a 150 ms data age deadline is only missed approximately half as often compared to when periodically alternating between left and right hand side transmission antennas. The methods have also been compared for different antenna combinations.