Cost-Minimizing System Design for Surveillance of Large, Inaccessible Agricultural Areas Using Drones of Limited Range

Abstract

Drones are used increasingly for agricultural surveillance. The limited flight range of drones poses a problem for surveillance of large, inaccessible areas. One possible solution is to place autonomous, solar-powered charging stations within the area of interest, where the drone can recharge during its mission. This paper designs and implements a software system for planning low-cost drone coverage of large areas. The software produces a feasible, cost-minimizing charging station placement, as well as a drone path specification. Multiple optimizations are required, which are formulated as integer linear programs. In extensive simulations, the resulting drone paths achieved 70–90 percent of theoretical optimal performance in terms of minimizing mission time for a given number of charging stations, for a variety of field configurations.

Soil Analysis via Remote Sensing and Artificial Intelligence for Precision Regenerative Agriculture

“…Euro" per hectare, per year, "a 10-15%" increase of viable crop growth, and a "10-17%" reduction in fertilizer application -all for "10 Euro" per hectare per year (Inoue, 2020). Tamayo et al (2020) incentivise using many drones to analyse agriculturally viable land with a theorized modular design. This design includes sun-powered recharging stations for drones limited by battery life, which is a common concern for the "surveillance of large, inaccessible areas", and would be included as a stop within its flight plan during the analysis mission (Tamayo et al, 2020).…”

“…Tamayo et al (2020) incentivise using many drones to analyse agriculturally viable land with a theorized modular design. This design includes sun-powered recharging stations for drones limited by battery life, which is a common concern for the "surveillance of large, inaccessible areas", and would be included as a stop within its flight plan during the analysis mission (Tamayo et al, 2020). Tamayo et al (2020) explore different configurations of recharging pads to optimize flight time.…”

“…This design includes sun-powered recharging stations for drones limited by battery life, which is a common concern for the "surveillance of large, inaccessible areas", and would be included as a stop within its flight plan during the analysis mission (Tamayo et al, 2020). Tamayo et al (2020) explore different configurations of recharging pads to optimize flight time. Chen et al (2022) show that conditional generative adversarial networks are generally suited to "data-driven geosciences".…”

A beginner's guide to infrastructure‐less networking concepts

“…A second large area concerns applications of UAVs (see the references given above), which often integrate techniques from artificial intelligence (e.g., computer vision) and optimization to determine tasks for individual UAVs, compute flight paths, and so on. In particular, (cooperative) path planning is a rich area of research, see for example, [150][151][152][153]. And of course, classical topics like routing have also received significant attention [154].…”

Intelligent Surveillance Drone System for Health Care Enhancement in a Smart City

“…Tamayo et al [22] presented the problem of agricultural surveillance using one drone with pre-defined paths, in addition to many charging stations that operate on solar energy and are distributed in predetermined locations, within irregular terrain that allows a limited number of locations for the installation of charging stations, to provide the drones with the required energy to carry out surveillance missions in large areas. The main goal of the agricultural surveillance process is to increase crop production by detecting early cultivation problems and taking the required proactive measures.…”