IoT-Assisted Livestock Management based on Edge Intelligence and automation

Overview

Optimises energy use in livestock stables while reducing animal heat stress, using IoT sensors for environmental monitoring, livestock behaviour assessment, and HVAC control. Data is collected, harmonised and processed at the edge to support energy use forecasting and optimisation considering efficient and stable milk production and ensuring animal welfare.

Expected Outcomes

• Improve the energy efficiency of dairy production processes, reducing total energy consumption per 1,000 kg of halloumi cheese by 20%, thereby contributing to more sustainable and cost-effective operations.
  • KPI: 20% reduction of total energy consumption for dairy production.
     
• To reduce the negative effects of heat stress on dairy cattle by 20%, improving animal welfare and maintaining stable milk production during hot months.
  • KPI: 20% reduction of heat stress impact on cattle.
     
• Improve energy efficiency and resilience in in‑farm milk production by enabling real‑time energy-aware monitoring and response to energy consumption to reduce costs and improve environmental sustainability.
  • KPI: Achieve  effective real‑time detection and reaction for at least 80% of relevant energy‑related energy events, from a baseline of no automated awareness or reaction capability.