Problem: Analyse energy usage (household/office) and provide real-time AI suggestions to reduce consumption and cost.

Context: Rising costs and environmental concerns make efficient energy use vital.

Deliverables: A functional web app/dashboard visualising usage and offering AI-driven recommendations (e.g., "Save 12% by adjusting appliance usage during off-peak hours").

Problem: Create an AI model to predict food waste based on inventory and purchasing, and recommend actions to reduce it (for homes/restaurants/supermarkets).

Context: Large amounts of food are wasted due to poor stock management.

Deliverables: A functional tool that ingests inventory data, predicts waste, and provides AI-driven recommendations (e.g., recipe suggestions, order adjustments).

Problem: Develop an app that estimates a user's carbon footprint (transport, diet, lifestyle) and uses AI to suggest practical reduction changes.

Context: People struggle to understand how daily habits contribute to their footprint.

Deliverables: A web/mobile app that calculates the footprint and offers personalised AI insights (e.g., "Switching to public transport twice a week could cut your carbon footprint by 18%").

Problem: Create a routing tool that suggests the most eco-friendly travel routes (public transport, walking, cycling, EV) and includes CO₂ comparison metrics.

Context: Transport is a major contributor to emissions; users need clear alternatives to the fastest routes.

Deliverables: A functional app generating multi-modal routes, displaying time, cost, and estimated CO₂ emissions (e.g., "Route B is recommended, cutting emissions by 57%").

Problem: Use open satellite data to map urban heat islands in a city. AI then recommends areas for shade/green spaces/cooling interventions.

Context: Cities are hotter than rural areas (heat islands), increasing energy demand and health risks.

Deliverables: A web app/dashboard that creates a visual heat map and offers AI-driven recommendations for high-impact intervention areas (e.g., "High priority zone. Recommended actions: plant street trees...").

Problem: Create a system to help small businesses map their supply chains and identify steps with the highest environmental impact using simple metrics.

Context: Small businesses need accessible tools to pinpoint environmental hotspots in their operations.

Deliverables: A web app/dashboard that inputs supply chain steps, assigns impact metrics (CO₂, water use), and visualises the highest-impact stages (e.g., "Step with highest impact: Transport from Supplier A to Warehouse").

Problem: Design an AI chatbot that gives personalised sustainability tips by analysing user data (house size, heating habits, appliance efficiency, usage).

Context: Generic advice is often unhelpful for individual circumstances.

Deliverables: A functional chatbot/web app that collects data, uses AI/rules to identify inefficiencies, and generates tailored advice (e.g., "Lowering thermostat settings by 1°C could save 8% annually.").

Problem: Analyse open city/environment datasets (air quality, noise, green spaces) to build a dashboard showing the sustainability health of neighbourhoods.

Context: Environmental data is often scattered and difficult for residents to interpret.

Deliverables: A web dashboard that connects to open data, aggregates it by neighbourhood, and displays a simple sustainability/liveability score and indicators (e.g., "Neighbourhood A: Sustainability score 78/100. Weakness: moderate air pollution.").

Problem: Create an AI system that generates long-term workforce sustainability insights by analysing hiring patterns, skills gaps, and potential biases.

Context: Organisational sustainability includes a balanced, resilient workforce.

Deliverables: A web app/dashboard that identifies skills gaps and bias risks, providing recommendations for improving workforce balance and diversity (e.g., "Significant skills gap in data and AI related roles...").

Problem: Create a web system that maps and analyses the distribution of green spaces across urban areas to identify regions with limited access.

Context: Access to nature is key for health and sustainability but is often unevenly distributed.

Deliverables: A web app/dashboard that visualises green space coverage, displays summary stats (e.g., average green space per person), and potentially offers recommendations for improvement.

Problem: Build a simple app that helps users track, visualise, and stay consistent with eco-friendly habits, using gamification and visualised impact.

Context: People struggle to maintain consistency and see the impact of small daily actions.

Deliverables: A web/mobile dashboard that logs actions, displays cumulative progress/streaks, estimates resource/CO₂ savings, and offers rewards/badges.

Problem: Develop a web app that helps users organise, join, and track local community clean-up events, visualising impact (waste collected, volunteers involved).

Context: Lack of a central platform for coordinating clean-up drives.

Deliverables: A web/mobile app that displays events, allows creation/joining, and tracks event outcomes, providing analytics (e.g., "Your community removed 500 kg of litter in June.").