In the last years, the Unmanned Aerial Vehicles (UAVs), also known as drones, are becoming always more attractive due to their capacity of a rapid deployment and their wide range of application in many real world scenarios. Among the various fields of application, recently, the use of drones in the precision agriculture is becoming much relevant for the researchers community. The studies related to agriculture concern different aspects such as livestock monitoring, crops and water levels. The drones are able to perform these tasks thank to a series of different sensors and actuators equipped on board. Cameras on board allow, through opportune algorithms, the gathering of detailed information about plants health. If a health problem is detected then the the drone can intervene precisely on the specific problem. The contribution of this work is a communication protocols analysis applied to the problem of controlling a fleet of drones against parasites attacks to the crops. Moreover, the study of the different approaches aims to measure their performance and costs. In particular, the various approaches face also the issues of exploring the area in the shortest time possible avoiding that the same area is explored from more drones, discovering the parasites and preventing their proliferation spraying the right quantity of pesticide. The drones, being equipped with limited quantities of both fuel and pesticide, can ask for help to other drones to complete the elimination of the parasites. To face these last issues some recruitment protocols have been tested, focusing on bio-inspired one.
In this paper, the attention is focused on the design of a decentralized Intelligent Transportation System (ITS) architecture in an Internet of Vehicle (IoV) environment. Introducing several independent Fog nodes, it is possible to take advantages of their computational properties for decreasing latency of the Centralized ITS Systems. Thus, a micro area controlled system is achieved. In this way, it will be possible to quickly and easily redesign ITS strategies. In this work, data coming from IoV layers are locally analyzed for checking anomalies by adopting mining algorithm. If something is going wrong, fog nodes locally face off the anomaly by taking a decision on incoming vehicle flow rates by choosing to limit or to completely block incoming traffic. In this work, we propose a cooperative strategy among decentralized ITS nodes for increasing safety and comfort of the drivers along their journeys. When local ITS policies fail, we propose a cooperative mechanism to find a macro-area optimized strategy. ITS node which detects issue will assume the role of master. Instead, neighbor fog nodes are involved by assuming the role of slave. Master node will decide policies and the slave node will apply these policies in the pertinent area. When issue is solved, the partnership is declared finished by the master. Each node returns master of their area. Moreover, this architecture is also based on a customized protocol for the IoV layer where Vehicle-to-Everythings (V2X) communications are optimized for assuring a good throughput and reducing interference.