Reduce household food waste by using intelligent technology
Households are responsible for about 40 to 50 percent of total food waste. Reduction of household food waste would save the global economy over £190 billion and significantly reduce carbon emissions. In this project, a low-cost, efficient system will be developed by combining new sensor technology and advanced artificial intelligence (AI) software on mobile devices. Most existing works on AI-enabled food waste reduction are mainly for retailers.
The proposal here focuses on domestic household food waste. The basic idea is to attach a cheap, AI-enabled lightweight electronic device to a user's fridge that can detect whether food is going bad and the “best before” date. AI-based software on smartphones will create smart recipes and shopping lists.
The proposed project holds great potential for a low-cost solution to reduce household food waste. It is expected the candidate who is interested in this project has a Master's degree in Electronic and Electrical Engineering and BEng degree in Electronic and Electrical Engineering with upper second or first class.
 Carlos Martin-Rios, Anastasia Hofmann and Naomi Mackenzie, “Sustainability-Oriented Innovations in Food Waste Management Technology”, Sustainability, No. 13, Vo. 210, 2021.
 Julie Liegeard and Louise Manning, “Use of Intelligent Applications to Reduce Household Food Waste”, Critical Reviews in Food Science and Nutrition, No. 6, Vol. 60, 2020.
How to apply
If you are interested in applying for the above PhD topic please follow the steps below:
- Contact the supervisor by email or phone to discuss your interest and find out if you woold be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
- Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
- Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.
This is a self funded topic
Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.
Meet the Supervisor(s)
- Dr Ruiheng Wu received his BEng and MEng degrees from Tianjin University, China, in 1982 and 1986 respectively. Following 10 years as a faculty member in the Department of Electronic Engineering at Tianjin University and two years research at the City University of Hong Kong, he joined the Analogue Circuit Design Research Group at Oxford Brookes University as a PhD student in January 1999, where he completed his PhD thesis entitled 'Design of Wide Bandwidth High Linearity Amplifiers'. In January 2002, he joined the School of Engineering, University of Greenwich, where he worked as a senior lecturer until January 2018. Between January 2018 and January 2020, Dr Wu worked in the School of Engineering and the Built Environment, Birmingham City University. Currently, Dr Wu is a senior lecturer in electronic and electrical engineering, Department of Electronic and Computer Engineering, Brunel University London. Dr Wu is a senior member of the IEEE and a member of the IET.
Dr. Lu Gan received her B. Eng and M. Eng. degrees from South East University, China and the Ph.D degree from Nanyang Technological University, Singapore in 1998, 2000 and 2004 respectively. She is currently a senior lecturer (equivalent to associate professor) in Brunel University, London. Before she joined Brunel University in 2008, she has been on the faculties with The University of Newcastle (2004-2006), Australia and University of Liverpool, UK (2006-2007). From 2003 to 2004, she was a research associate in Centre for Signal Processing, Nanyang Technological University.
Dr. Gan’s research interests include fundamental signal processing theories and their applications in image/video coding and processing, non-destructive terahertz and ultrasound imaging, machine learning and wireless communications etc. Her research work has been funded by Australian research council, The Engineering and Physical Sciences Research Council (EPSRC) UK and TWI UK. She is a member of IEEE and a regular reviewer for many top journals including IEEE Transactions on Information theory, IEEE Transactions on Signal Processing, IEEE transactions on Communications and IEEE transactions on image processing etc. She has also been reviewing research grants in UK EPSRC and UK STFC and FWO in Belgium (equivalent to EPSRC in UK). She has been on the technical committee member for conferences including Globecom and ICC.
So far, she has more than 30 publications on journals with high impact factor and more than 60 conference publications. She has been working as Ph. D thesis/viva examiner for more than 20 candidates in UK and Australia. Her google scholar file can be found here.