Choose one track. Master’s proposals target Spring 2027. Final scope and programme approval are agreed with the supervisor; bachelor scopes are suggested adaptations.
TRACK 01 · IMPLEMENTATION INCLUDED
Technical track
Develop a working solution and test whether it addresses the problem.
Possible research question
How can AI-supported planning reduce energy use or peak demand while respecting comfort and operational requirements?
Suggested tasks
Read research on energy planning in public buildings and compare existing solutions.
Identify one problem faced by facility managers.
Write a research question and define what the solution should do.
Use existing or simulated energy readings to predict demand in one public building.
Build a tool that suggests heating or operating schedules and lets the building manager adjust them.
Compare suggested schedules with a fixed schedule. Measure energy use and whether comfort requirements are met.
Explain what worked, what did not, and how the results compare with earlier research.
Evaluation, degree scope and deliverables
Study and evaluation
Compare the implemented solution with a fixed schedule and, where feasible, a conventional constrained optimiser. Combine reproducible technical tests with an appropriate empirical evaluation.
Simulated energy use or peak demand
Comfort and operational constraint violations
Effort to understand and approve plans
Degree scope
Bachelor’s
Build a scheduling interface around one building model and a simple forecast. Test comfort constraints and the clarity of proposed changes.
Master’s
Compare human-controlled planning strategies using replay or simulation and study how managers interpret uncertainty and trade-offs.
Background
Programming
Time-series analysis
Basic ML; optimisation is useful
Possible deliverables
A focused literature review, justified problem and research question
A working prototype with source code and setup instructions
A reproducible comparison and an appropriate study of use
A report explaining design lessons, results and limitations
TRACK 02 · NO IMPLEMENTATION REQUIRED
Non-technical track
Study existing systems, information or work practices. You do not need to develop software.
Possible research question
What makes AI-supported energy recommendations understandable and acceptable to facility managers?
Suggested tasks
Read earlier studies of energy planning in public buildings.
Choose one problem and write a research question the study can answer.
Interview managers about comfort requirements, operational constraints and decision authority.
Discuss alternative schedules and existing energy reports using a fictional or authorised building case.
Analyse when recommendations are accepted, adapted or rejected and which explanations matter.
Analyse the interviews, observations or documents using a clearly described method. Look for disagreements as well as common patterns.
Explain the findings, compare them with earlier research and suggest practical improvements.
Evaluation, degree scope and deliverables
Study and evaluation
Use a bounded empirical study of energy planning in public buildings. Justify case selection, recruitment and the analysis method. Distinguish observed behaviour from participants’ perceptions; use triangulation or a comparison where it serves the research question.
Trade-off reasoning and conditions for adoption
Perceived control, accountability and workflow fit
Evidence for the findings, conflicting cases and limits of the study
Degree scope
Bachelor’s
Study one case or a small set of existing materials. Agree the interviews, documents or scenario tasks with the supervisor. Describe the method, analyse the findings and give practical recommendations.
Master’s
Use a clear research question and relevant IS theory. Justify the cases, participants and analysis method. Explain what the findings add to earlier research and where they may apply. No software development is required.
Background
Literature review and academic writing
Qualitative or quantitative research methods
Interest in energy planning in public buildings; no programming prerequisite
Possible deliverables
A literature review and research question
A study plan and approved research material
An analysis supported by interviews, observations, documents or scenario results
A thesis with findings, recommendations and limitations
Scope and access
One building, one planning horizon and a few schedules. Reinforcement learning is optional and evaluated offline. Autonomous control of a real building is outside the core scope. These implementation-related limits apply when developing or testing a technical solution. For a non-technical study, agree access to participants or existing materials early, use approved or fictional cases where appropriate, and distinguish perceptions from observed outcomes.
Agree access to data, participants or existing materials and any required ethics or privacy review before committing. A non-technical track needs a systematic study, not a working prototype.
Full academic proposal
Working topic
Human-Controlled AI Planning for Energy Use in Public Buildings
Brief outline
This proposal examines energy planning in public buildings in the work and information needs of facility managers. The technical track combines a literature review and justified gap with requirements, design, implementation and evaluation of a bounded solution. The non-technical track investigates practices, experiences or organisational conditions through a systematic study of existing systems, documents or scenarios, without requiring implementation. Choose one track and agree the final research question, degree scope and contribution with the supervisor.
Programme fit
Information Systems. These are suggested research approaches, not a statement of confirmed programme policy. Agree the final title, track, degree scope and contribution with the supervisor and programme.
Shared research foundation
Review the literature; identify and justify a gap; formulate research questions; conduct a systematic study; analyse the evidence; explain the contribution relative to prior research and discuss limitations. The technical track additionally includes requirements, design, implementation and evaluation of an artifact.
