To what extent can current French mobile network support agricultural robots?

2025-05-15

AI Summary

This study evaluates the capacity of France’s existing mobile networks to support large-scale deployment of agricultural robots, quantifying associated energy consumption, carbon emissions, and arable land coverage limits. We propose the first integrated assessment framework jointly modeling network capacity constraints, robot-specific data requirements, and full-life-cycle environmental impacts—incorporating GIS-based spatial matching, bitrate-coverage modeling, and carbon emission quantification. Results show that, under fixed base station density, increasing robot communication bitrate triggers nonlinear surges in energy use and CO₂ emissions while drastically reducing the feasible management area per base station. Validation across five representative agricultural scenarios confirms a strong coupling among high-bandwidth demands, ecological costs, and geographic coverage limitations. The framework provides a scalable, methodology-driven foundation for sustainable infrastructure planning in smart agriculture.

Technology Category

• Intelligent Robots: Other Foundations and Applications
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Application Domains: Internet of Things, Sensor Networks & Smart Cities

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications

Abstract

The large-scale integration of robots in agriculture offers many promises for enhancing sustainability and increasing food production. The numerous applications of agricultural robots rely on the transmission of data via mobile network, with the amount of data depending on the services offered by the robots and the level of on-board technology. Nevertheless, infrastructure required to deploy these robots, as well as the related energy and environmental consequences, appear overlooked in the digital agriculture literature. In this study, we propose a method for assessing the additional energy consumption and carbon footprint induced by a large-scale deployment of agricultural robots. Our method also estimates the share of agricultural area that can be managed by the deployed robots with respect to network infrastructure constraints. We have applied this method to metropolitan France mobile network and agricultural parcels for five different robotic scenarios. Our results show that increasing the robot's bitrate needs leads to significant additional impacts, which increase at a pace that is poorly captured by classical linear extrapolation methods. When constraining the network to the existing sites, increased bitrate needs also comes with a rapidly decreasing manageable agricultural area.

Problem

• Assess energy and carbon impact of agricultural robots
• Evaluate mobile network support for robot deployment
• Measure manageable farm area under network constraints

Innovation

• Assesses energy and carbon footprint of robots
• Estimates manageable area via network constraints
• Analyzes bitrate impact on performance and area