An automated tool was developed to quantify plate waste in primary school canteens, with data collected from 421,015 instances of food wastage. The tool showed high accuracy, with plate waste detection within ±10% of manual recordings. However, it estimated 40% fewer individual guests compared to manual entry, leading to a 35% higher waste-to-guest ratio. The study found that 20% of students accounted for 60% of plate waste, indicating that targeted interventions for high-waste students could significantly reduce overall waste. The tool used weighing scales connected to a tablet computer to track waste, providing real-time feedback to guests. It also allowed guests to provide feedback on why they wasted food, which was analyzed to understand waste patterns. The tool detected waste more accurately than manual methods, but the number of guests recorded was lower, leading to a higher waste-to-guest ratio. The study highlights the importance of focusing on high-waste individuals rather than applying general measures to all students. Automated tools offer a more efficient way to monitor and reduce food waste, but they should be used in conjunction with manual methods to ensure accurate data. The findings suggest that targeted interventions for high-waste students could significantly reduce food waste in school canteens.An automated tool was developed to quantify plate waste in primary school canteens, with data collected from 421,015 instances of food wastage. The tool showed high accuracy, with plate waste detection within ±10% of manual recordings. However, it estimated 40% fewer individual guests compared to manual entry, leading to a 35% higher waste-to-guest ratio. The study found that 20% of students accounted for 60% of plate waste, indicating that targeted interventions for high-waste students could significantly reduce overall waste. The tool used weighing scales connected to a tablet computer to track waste, providing real-time feedback to guests. It also allowed guests to provide feedback on why they wasted food, which was analyzed to understand waste patterns. The tool detected waste more accurately than manual methods, but the number of guests recorded was lower, leading to a higher waste-to-guest ratio. The study highlights the importance of focusing on high-waste individuals rather than applying general measures to all students. Automated tools offer a more efficient way to monitor and reduce food waste, but they should be used in conjunction with manual methods to ensure accurate data. The findings suggest that targeted interventions for high-waste students could significantly reduce food waste in school canteens.