Integrating IoT and Simulation for Efficient Livestock Waste Spread in the Po Valley

The livestock industry in the Po Valley is economically significant but generates challenging by-products, notably pig manure. Disposal typically involves spreading manure on agricultural land, requiring daily transportation by hundreds of tankers and leading to soil, water, and air pollution. This method incurs high costs and poses monitoring challenges for government agencies. This research develops a simulated environment that mimics waste dissemination activities in the Po Valley to support the development of an Internet of Things (IoT) architecture for cost-effective environmental monitoring. A custom-built emulator was designed to map driver behaviors, identify limitations, and foresee challenges before real-world implementation, enabling scalable completely renovated and distributed monitoring tools.

Authors

Institutions

Publication Details

Published
2024-10-07
DOI
https://doi.org/10.1109/ds-rt62209.2024.00034
Citations
2
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
1.20
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating IoT and Simulation for Efficient Livestock Waste Spread in the Po Valley

Marco Picone, Marko Bertogna, Giovanni Triboli
2 citations
Smart Agriculture and AI
1.20
article

Integrating IoT and Simulation for Efficient Livestock Waste Spread in the Po Valley

Marco Picone, Marko Bertogna, Giovanni Triboli
article en
2 citations

Abstract

The livestock industry in the Po Valley is economically significant but generates challenging by-products, notably pig manure. Disposal typically involves spreading manure on agricultural land, requiring daily transportation by hundreds of tankers and leading to soil, water, and air pollution. This method incurs high costs and poses monitoring challenges for government agencies. This research develops a simulated environment that mimics waste dissemination activities in the Po Valley to support the development of an Internet of Things (IoT) architecture for cost-effective environmental monitoring. A custom-built emulator was designed to map driver behaviors, identify limitations, and foresee challenges before real-world implementation, enabling scalable completely renovated and distributed monitoring tools.

University of Modena and Reggio Emilia (IT)
Openalex Percentile: Top 15%
Smart Agriculture and AI
1.20
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.