There is a lack of knowledge among food manufacturers about adopting the Internet of Things (IoT)-based water monitoring system and its ability to support water minimisation activities. It is therefore necessary to investigate the applicability of IoT-based real-time water monitoring systems in a real food manufacturing environment to pursue water-saving opportunities accordingly. This article aims to propose an architecture of an IoT-based water-monitoring system needed for real-time monitoring of water usage, and address any water inefficiencies within food manufacturing. This article looks at a study conducted in a food beverage factory where an IoT-based real-time water monitoring system is implemented to analyse the complete water usage in order to devise solutions and address water overconsumption/wastage during the manufacturing process. The successful implementation of an IoT-based real-time water monitoring system offered the beverage factory a detailed analysis of the water consumption and insights into the water hotspots that needed attention. This action initiated several water-saving project opportunities, which contributed to the improvement of water sustainability and led to an 11% reduction in the beverage factory’s daily water usage.

Future energy systems must mainly generate electricity from renewable resources. To deal with the fluctuating availability of wind and solar power, new versatile electricity markets and sustainable solutions concentrating on energy flexibility are needed. In this research, we investigated the potential of energy flexibility achieved through demand-side response for the wastewater treatment plant of the Benchmark Simulation Model 1. First, seven control strategies were simulated and assessed. Next, the flexibility calls were identified, two energy flexibility scenarios were defined and incorporated into the model, and the control strategies were evaluated anew. In this research, the effluent ammonia concentration needed to be maintained within the limits for as long as possible. Strategy 5, which controlled ammonia in Tank 5 at a low value and did not control any nitrate in Tank 2, of Scenario 1, which was characterized by an undetermined on/off aeration cycle, was then found to be the best. Although this control strategy led to high total energy consumption, the percentage of time during which aeration was nearly suspended was one of the highest. This work proposes a methodology that will be useful to plant operators who should soon reduce energy consumption during spikes in electricity prices.