Problem statements.

Cargo terminals, warehouses, yards and logistics facilities struggle with material movement, inventory visibility, operational delays, workplace safety and resource utilisation. Manual handling and fragmented monitoring reduce productivity and increase the risk of errors and accidents. Autonomous robots can help, but they must cope with obstacles, restricted pathways, changing surroundings and uncertain sensor information, all of which affect navigation reliability and operational safety.

Develop an intelligent autonomous system that improves the efficiency, safety or coordination of cargo handling in a defined operating environment. The system should perceive its surroundings, move through a constrained space and respond appropriately when conditions change.

• Material movement and inventory visibility
• Safety of people, equipment and cargo
• Different operating environments (terminal, warehouse, yard)
• Obstacle handling and changing surroundings
• Uncertain or noisy sensor information
• Navigation safety constraints and repeatability

• A working proof of concept (PoC) for a clearly identified cargo-handling or logistics problem, including autonomous movement or navigation in a representative environment
• Demonstration under representative operating conditions, using a physical platform, scaled environment or suitable simulation
• Evaluation of efficiency, safety, reliability or resource utilisation, together with navigation success, obstacle handling and repeatability
• Evidence of feasibility for deployment in a relevant logistics environment, with safety constraints and conditions needing further testing identified

Farmers need timely information on crop condition, soil characteristics, irrigation needs, weeds and other field-level variations. Small and medium farms often cannot afford automation and precision-farming technologies.

Build an affordable system that monitors or supports a specific agricultural task on small and medium farms.

• Affordability for small and medium farms
• Varying terrain and environmental conditions
• Practical farm requirements and ease of use

• A PoC demonstrating a specific agricultural task or field-monitoring capability
• Validation using representative crops, soil conditions, field data or a suitable test environment
• Assessment of usability, reliability and resource efficiency
• Documentation of applicability to small and medium farms

Unexpected failures in motors, pumps, compressors and other industrial equipment cause downtime, maintenance costs, production losses and safety concerns. Fixed maintenance schedules often do not reflect the actual condition of the equipment. Facilities also lack a single view that links equipment condition with utility consumption such as electricity, water and compressed air, which makes it hard to spot waste and prioritise maintenance.

Use equipment-condition information to identify abnormal behaviour, assess degradation and support better maintenance decisions. Present the results, together with utility consumption, on a utility dashboard that operators and maintenance teams can use.

• Source of condition data (sensors, lab setup, recorded data)
• Balance between detection accuracy and false alarms
• Response time and usefulness for maintenance planning
• Utility dashboard design: clear display of equipment health, alerts and utility usage (electricity, water, compressed air)

• A working PoC for equipment-condition assessment or early detection of abnormal behaviour
• A utility dashboard that shows equipment condition, alerts and utility-consumption trends in a form operators and maintenance planners can act on
• Validation using measured data, a laboratory setup, recorded operating data or controlled fault conditions
• Performance evaluation using indicators such as detection accuracy, false alarms and response time
• Assessment of the potential to reduce unplanned downtime, cut utility waste or improve maintenance planning

Buildings, bridges and other civil infrastructure face ageing, environmental stress, repeated loading and unexpected events. Detecting deterioration before it becomes critical is essential for public safety and infrastructure management.

Assess the condition of a structure over time and present the information in a form that supports inspection, interpretation and maintenance decisions.

• Choice of structure, specimen, simulated data or real dataset
• Clear presentation of structural-condition information
• Identifying significant changes over time

• A PoC for monitoring or assessing a selected structural or infrastructure condition
• Demonstration using a model structure, laboratory specimen, simulated data or a suitable real-world dataset
• A way to present structural-condition information and flag potentially significant changes
• Evaluation of limitations, reliability and suitability for further testing

Drainage and sewer networks develop blockages, cracks, sediment build-up, corrosion and other defects that are hard to inspect manually. Confined spaces, hazardous gases, poor visibility and restricted access put maintenance workers at risk.

Develop a way to assess the condition of drainage infrastructure and locate maintenance needs while reducing human exposure to hazardous environments.

• Confined spaces and limited visibility
• Detecting and recording defects and obstructions
• Practical constraints of real drainage networks

• A PoC demonstrating inspection or condition assessment in a representative drainage environment
• Identification or recording of relevant defects, obstructions or abnormal conditions
• Demonstration in a test section that represents selected field constraints
• Evaluation of inspection coverage, reliability and deployment challenges

Electric vehicle batteries must operate within safe electrical and thermal limits. Differences in battery condition, charging behaviour, cell imbalance and temperature affect performance, service life and safety.

Assess battery operating information to improve visibility of battery condition, identify abnormal behaviour and support safer charging and utilisation.

• Cell imbalance, temperature and charging behaviour
• Accuracy and responsiveness of monitoring
• Safety considerations before any real deployment

• A PoC for battery-condition monitoring or identification of selected abnormal operating conditions
• Validation using a battery test setup, battery simulator or representative data
• Assessment of the accuracy and responsiveness of the monitoring approach
• Documentation of safety considerations and limitations before practical deployment

Manufacturers must detect defects, dimensional deviations, assembly errors and material inconsistencies without slowing production. Manual inspection is time-consuming and can be inconsistent, especially when products or operating conditions vary.

Improve defect identification, quality assessment and inspection consistency for a clearly defined manufacturing process.

• Variation in product appearance and operating conditions
• Repeatability and error rates
• Impact on throughput and material waste

• A PoC for a clearly defined manufacturing inspection or quality-control task
• Demonstration using representative products, samples, images or test data
• Evaluation of inspection performance, repeatability and relevant error rates
• Assessment of the potential to improve quality assurance and reduce avoidable waste

Getting the most from solar power is difficult before and after installation. Before installation, the suitability of a rooftop depends on roof geometry, orientation, shading, available area and local solar conditions, and assessing these factors for individual buildings or entire urban areas is resource-intensive. After installation, solar systems lose output due to dust, shading, damaged modules, electrical faults and other factors, and inspecting large or hard-to-reach installations takes considerable time and effort.

Develop a solution that helps plan, inspect or maintain solar power on buildings: estimate rooftop solar potential, assess the condition of an installed system, identify performance-related issues and support timely maintenance without compromising safety or equipment integrity. Teams may focus on one part of this chain or link both, and should communicate findings clearly to building owners, planners, operators or energy stakeholders.

• Data sources (building geometry, imagery, solar data, measurements) and clearly documented assumptions
• Identifying and classifying conditions that reduce performance
• Safety of personnel and equipment
• Prioritising maintenance for the greatest energy-yield benefit
• Usefulness of results for solar planning and operation

• A PoC for assessing the solar potential of selected buildings, or for inspection, condition assessment or maintenance prioritisation in a representative solar installation (or both)
• Demonstration using building geometry, solar data, imagery, physical measurements, a panel test setup, a simulated installation or operational data
• Estimates of installable area or energy generation with assumptions documented, and/or identification or classification of selected conditions that affect performance
• Evaluation of accuracy, inspection effectiveness, practical constraints and potential energy-yield benefits

Underwater environments, reservoirs, water tanks and coastal ecosystems need inspection for structural defects, sediment accumulation, water-quality changes and environmental disturbance. Poor visibility, currents, communication limits and risks to human divers make this difficult.

Collect useful underwater information and assess selected conditions in a controlled or representative aquatic environment.

• Limited visibility and water currents
• Communication and control underwater
• Stability and repeatability of observations

• A PoC demonstrating an underwater inspection, observation or environmental-monitoring task
• Validation in a water tank, pool or other controlled aquatic environment
• Collection and interpretation of relevant observations or measurements
• Evaluation of stability, repeatability, coverage and constraints for future field trials

Water from bathing, handwashing and laundry offers a major reuse opportunity once suitably treated. However, varying contaminants, treatment needs, storage conditions and intended uses limit safe reuse.

Assess, treat or manage greywater so that its reuse potential can be evaluated for appropriate non-potable applications.

• Variation in contaminants and intended use
• Water-quality indicators before and after treatment
• Storage, operation and environmental considerations

• A PoC demonstrating a selected greywater assessment, treatment or reuse process
• Evaluation using representative greywater or a controlled test mixture
• Measurement of relevant water-quality indicators before and after the process
• Assessment of reuse suitability, operational requirements and environmental impact

Railway infrastructure faces repeated mechanical loading, environmental effects and material degradation. Defects, wear and changes in track condition can affect safety and reliability if not identified in time.

Assess selected rail or track conditions, detect abnormal indications and support inspection prioritisation. Important: any prototype must be evaluated in a controlled environment and must not be treated as a substitute for certified railway safety inspection.

• Distinguishing normal from abnormal conditions
• Detection consistency
• Requirements for further safety validation

• A PoC for identifying or assessing a selected rail or track-condition indicator
• Validation using test specimens, controlled measurements or representative datasets
• Evaluation of detection consistency and the ability to separate normal from abnormal conditions
• Assessment of potential inspection applications and the further safety validation needed

Electric drives in pumps, fans, conveyors and small machines consume energy according to load, speed, control method and mechanical condition. Inefficient operation and unnecessary running raise energy costs and equipment stress.

Identify the factors that drive energy consumption in a drive system and improve efficiency without compromising required performance.

• Load, speed, control method and mechanical condition
• A clearly defined baseline for comparison
• Trade-offs between energy saving and performance

• A PoC addressing an identified drive-system efficiency or energy-management problem
• Measurement of electrical input and relevant mechanical or operational performance
• Comparison against a clearly defined baseline under comparable operating conditions
• Assessment of energy-saving potential, performance trade-offs and feasibility

Mixed waste contains recyclable, biodegradable, hazardous and residual materials. Poor segregation reduces material recovery, raises processing costs and creates environmental and occupational hazards. Waste composition also differs between households, campuses, commercial facilities and industrial sites.

Improve waste identification, segregation or recovery in a defined waste-management context.

• Throughput and contamination
• Variation in waste composition across settings
• Operating constraints and safety requirements

• A PoC for a clearly defined waste-segregation or material-recovery task
• Demonstration using representative waste samples or a controlled test stream
• Evaluation of segregation effectiveness, contamination and processing performance
• Assessment of resource-recovery potential, feasibility and safety requirements

Agricultural fields, industrial sites and infrastructure assets need periodic inspection for damage, deterioration and maintenance needs. Manual inspection of large, elevated or inaccessible locations is slow and difficult. Aerial platforms can help, but their usefulness depends on the inspection goal, data quality, operating environment and safety requirements.

Show how aerial observations can support a clearly defined inspection or monitoring task.

• A clear inspection objective
• Data quality and coverage
• Safety constraints and applicable regulations

• A PoC demonstrating an aerial inspection or observation task for a selected application
• Validation in a controlled flight environment, suitable test area or with representative aerial data
• Demonstration of how the collected information supports identification or assessment of conditions
• Evaluation of coverage, data quality, safety constraints and feasibility

Not every important problem fits a list. If your team has spotted a real, unsolved problem that matters to people, industry, society or the environment, you are welcome to propose it as your own problem statement. It can fall in any engineering or technology domain, including areas not covered by the problem statements above.

Identify a real-world problem, justify why it matters, and design and demonstrate a technically sound solution as a proof of concept.

• Who is affected by the problem, and how serious is it?
• Which UN Sustainable Development Goals (SDGs) does it support?
• Can a working PoC realistically be built and tested within the programme timeline?
• What makes your approach better than existing solutions?

• A clear problem definition, supported by evidence or observation from the field
• A working PoC, with validation using a test setup, simulation or representative data
• Evaluation of performance, reliability, feasibility and limitations
• A mapping to relevant SDGs, with a note on potential impact and the path to a market-ready product