Explore digital twin smart building comfort optimization through a published research reference related to Pollution Control / Air Quality. This M.Tech resource summarizes the available source and suggests questions to validate before choosing an implementation.
Digital twin smart building comfort optimization: source and project details
| Research overview |
This research tackles the hard problem of balancing several comfort factors with energy use in shared, multi‑occupant buildings. In these cyber‑physical systems, the physical environment, human behavior, and software controls are tightly linked. Comfort depends on multiple interrelated things—temperature, noise level, indoor air quality, and how crowded a space feels. Changing one factor can unintentionally worsen another; for example, increasing ventilation to improve air quality can shift indoor temperatures and hurt thermal comfort. Because both the environment and occupants’ preferences vary over time, fixed control settings aren’t enough.
The indexed metadata proposes a digital‑twin‑driven way to manage these dynamic interactions, though the abstract does not give full algorithm details, experimental validation, or control architecture. For M.Tech researchers, this framework offers a solid base for building co‑simulation models that couple building‑energy simulation tools with multi‑objective optimization algorithms. By representing occupants as dynamic agents within a digital twin, researchers can explore trade‑offs among indoor air quality, thermal comfort, and HVAC energy consumption under different occupancy scenarios.
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| Reference Thesis |
A digital twin-driven approach for multi-modal individual comfort and energy optimization in multi-occupant environments |
| Publication year (source record) |
2026 |
| Source document classification |
Academic thesis/dissertation (not a journal article) |
| Discovered via |
HAL metadata |
| Authors (source metadata) |
Jun Ma |
| Publication type (source metadata) |
doctoral-thesis |
| Metadata consistency check |
Independent publisher/registry metadata comparison unavailable; editorial source verification required. |
| Evidence reviewed by generator |
Indexed abstract/description only; original full text, author names in PDF and methods require editorial verification. |
| Domain |
Environmental Engineering |
| Sub-Domain |
Pollution Control / Air Quality |
| Research source |
View research PDF |
| Get Help |
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Message: Hi FE, I need help with “A digital twin-driven approach for multi-modal individual comfort and energy optimization in multi-occupant environments” in “Environmental Engineering”
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Project or research direction
This source is a thesis/dissertation, not a verified implementation blueprint. Use it to identify research questions and supporting literature before choosing a build.
Possible tools or components to evaluate
EnergyPlus, MATLAB/Simulink, Python (for optimization algorithms), BCVTB (Building Controls Virtual Test Bed), Functional Mock-up Units (FMUs)
Outputs to plan and verify
A simulation-based digital twin framework demonstrating the trade-offs between multi-modal occupant comfort and HVAC energy consumption, showing optimized ventilation rates and temperature setpoints under varying occupancy profiles.
Suggested verification steps
- Read the cited paper and check which methods, parameters and results it actually reports.
- Define a measurable project objective and list equipment or software you can access.
- Validate the proposed approach independently before claiming results, working code or experimental success.
Implementation ideas above are planning suggestions, not claims that the cited researchers built or tested those exact extensions.
Explore related M.Tech project topics or browse the engineering resource library for different methods and reference papers.
