Utilising the Internet of Things concepts to improve the resource efficiency of food manufacturing

Sammanfattning: This thesis reports on the research undertaken to increase the sustainability of foodmanufacturing by reducing the solid Food waste generation, as well as Energy and Water(FEW) consumptions through applications based of Internet of Things (IoT) concepts. Theprimary objective of this research is to develop an IoT-based framework, which identifies andcollects the key data regarding FEW within food manufacturing. The other objective is todesign and implement a decision support tool using appropriate and existing hardware andsoftware to aid the stakeholders with the choice of the most effective solution to reduce theFEW within food manufacturing processes.The research contributions are divided into four main parts. The first part reviews the relevantliterature on the current state of FEW in food manufacturing, their environmental impacts, andreasons behind their generation, opportunities to reduce FEW and applications of IoT withinfood manufacturing. The second part introduces the IoT-based framework to address themonitoring of FEW. This framework was developed since most of the food manufacturers arenot aware/or ignorant of their FEW and its environmental and financial value. The third partdescribes the implementation of the framework through an architectural prototype developedusing a combination of software and hardware. The final part of the thesis demonstrates theapplication of the IoT tool to monitor the FEW in real-time using case studies and therebysupport the management decisions aimed at reducing FEW.The industrial application of the research concepts proposed in this thesis through four specificcase studies has highlighted the complexities as well as the opportunities available in usingdigital technologies in improving the overall sustainability of the food sector. This is due to thevariety and specific nature of the food products as well as a large number of small to mediumscale enterprises that form a significant proportion of the supply chain in this sector.In summary, this research has provided a practical and powerful tool based on IoT conceptsto address the FEW within food manufacturing. This research has concluded that theconsideration of the FEW reductions within the food industry requires an accurate, detailedand real-time based understanding of FEW in order to allow stakeholders to take proactiveapproaches in FEW reductions.