Exploring Aerial-IoT possibilities: combining UAVs and IoT for more effective environmental monitoring

Environmental monitoring in both industrial, rural urban districts, as well as in forests, is crucial for understanding, monitoring and mitigating the impact of human activities on existing ecosystems.

Traditional monitoring methods often face limitations such as accessibility, infrastructure cost, and coverage, as well as long deployment times.  Autonomous flying drones equipped with on-board sensors, Global Navigation Satellite System (GNSS) as well as the ability to deploy battery powered smart sensors or to connect to in-field sensing nodes already available, offer a promising solution to overcome these challenges.  

Drones as IoT gateways for ground level monitoring in poor coverage areas 

In a forestry environment scenario as depicted in Figure 1, by exploiting the autonomous flight capabilities of drones connected to, through the existing 5G cellular networks, the cloud infrastructure, it is possible to both process the gathered data as well as to control the flight path of the autonomous drone along the target area. Furthermore, to enable ground level monitoring, the drone can carry some IoT sensing nodes to be deployed in the forestry environment, by dropping them during the autonomous flight in the desidered points.

Figure 1: Autonomous drone flying over a forest to gather data transmitted by the deployed sensing nodes.

In this way, the dropped sensors, as well as the manually deployed sensors in the target environment, can collect critical data for several hours and communicate them with the drone performing a scheduled autonomous flight a few decades of meter higher than ground level, thus enabling aerial-IoT connectivity involving the 5G connected drone as a wireless relay (using various heterogeneous wireless protocols, like Wi-Fi, BLE or LoRa) to exhcnage data with the ground located devices, which are not able to directly communicate with the existing cellular or IoT infrastructure due to the high vegetation or obstacle density.


The aforementioned sensing nodes can be equipped with multiple sensors, suitable to allow humidity, temperature and air monitoring, as well as a long-lasting battery that, according to the data collection rate, allows them to work up to several days. In order to communicate with the UAV while preserving the battery life, scheduled communication windows with the drone happen only a few times a day or a week, with only the anomalous and critical data sent to the nearby drone using different wireless technology based on both the distance between the two parts of the communication as well as the amount of data to transfer. All the data gathered by the drone are then sent to the cloud infrastructure using LTE or 5G cellular connectivity, where the data are then processed and plotted on a dashboard to be visualised by the operator and authorities.


Aerial-IoT for critical site survey missions 

In the industrial and rural city scenario, autonomous flying drones equipped with multiple type of connectivity can be exploited to communicate with in-field nodes during surveys and critical mission, where the in-field sensor data, together with on-board sensors located on the drone, can provide additional information suitable to perform a deeper survey of the industrial site, as well as monitor rural urban areas. 


As for the forestry scenario, in-field sensing nodes can directly communicate with the communication wireless infrastructure using cellular or LoRaWAN technologies, while point-to-point communications with the nearby drone can be enabled using BLE, Wi-Fi or LoRa, based on the operating range as well as the amount of data to transmit. Once the data are collected by the drone, they are transmitted to the cloud platform through 5G cellular networks, where they are processed in order to detect anomalies and alert authorities. A representation of the mentioned scenario is depicted in Figure 2.

Figure 2: Autonomous drone flying over an industrial and rural urban area to gather data transmitted by the deployed sensing nodes and detect anomalies.