Artificial intelligence (AI) has a crucial role to play in the future of sustainability, with unprecedented ability to process, analyse and interpret large datasets, driving innovation in many areas including health, waste management and resource optimization. Our Imaging and Computer Vision Lancaster (iCVL) research group is focused on developing world-leading research in AI methodology and dedicated to integrating sustainability into our research ethos. Led by Dr Bryan M. Williams and Dr Hossein Rahmani, our work is centred on developing cutting-edge algorithms and AI models targeted at tackling challenges in health inequality, justice and environmental waste.
Health Inequalities
Access to affordable and preventative healthcare is a key challenge in addressing global health inequalities. Our work in medical imaging focuses on developing automated image analysis and diagnosis techniques capable of state-of-the-art results with lower-cost devices. This enables us to bring diagnosis and treatment recommendations to areas lacking the necessary expertise, as well as reducing the burden on NHS resources which has risen to unprecedented levels in the wake of the COVID-19 pandemic. Together with universities and hospital trusts around the world, we have also developed workshops and courses in AI to engage both medical practitioners and the public to increase awareness and maximise impact of this work.
Justice
Resource limitations and knowledge gaps in forensic science threaten to undermine social justice. Our work in biometric identification is targeted at developing methodologies that can provide confidence in their security, accuracy, and reliability, building from solid foundations in AI and human anatomy. Our flagship interdisciplinary project H-Unique is developing the first multimodal interrogation of visible hand anatomy, though the analysis of human variation and development of machine learning theory. This will drive a step-change in the science of anatomical variation and provide robust support for the accurate identification of individuals. This work has wide-ranging interdisciplinary and transdisciplinary impact for the key sustainable development goal of providing peace, justice, and strong institutions, with a particular focus on the crime of child sexual abuse, where evidence often includes images of the hand with no other identifiable information.
Environmental Waste
Approximately 800 new illegal large-scale dumping sites appear every year in the UK, and numbers have grown threefold since 2020, contributing significantly to environmental pollution. Environment agencies and councils have finite resources to tackle this issue and clear needs have been identified in ensuring quick responses to fly-tipping events and maximising front-line efficiencies. Working with Lancaster City Council and Station10, we have developed accurate industrial fly-tipping identification techniques, allowing stakeholders to better deploy their already-stretched resources to tackle waste crime. We will also help to predict future tipping events to inform enforcement and risk mitigation strategies for preventing industrial waste crime and broader strategies to drive long-term behavioural change.
Future Sustainability
Our work in AI is essential to building a sustainable future that benefits both the planet and its inhabitants, when integrated responsibly, ethically, transparently, and with human oversight. Addressing these challenges requires a multi-faceted approach. Our challenge is to develop the core future research toward achieving sustainable justice, health, and environment worldwide.