Regularized Deconvolution-Based Approaches for Estimating Room Occupancies
2015 (English)In: IEEE Transactions on Automation Science and Engineering, ISSN 1545-5955, E-ISSN 1558-3783, Vol. 12, no 4, 1157-1168 p.Article in journal (Refereed) Published
We address the problem of estimating the number of people in a room using information available in standard HVAC systems. We propose an estimation scheme based on two phases. In the first phase, we assume the availability of pilot data and identify a model for the dynamic relations occurring between occupancy levels, CO2 concentration and room temperature. In the second phase, we make use of the identified model to formulate the occupancy estimation task as a deconvolution problem. In particular, we aim at obtaining an estimated occupancy pattern by trading off between adherence to the current measurements and regularity of the pattern. To achieve this goal, we employ a special instance of the so-called fused lasso estimator, which promotes piecewise constant estimates by including an l(1) norm-dependent term in the associated cost function. We extend the proposed estimator to include different sources of information, such as actuation of the ventilation system and door opening/closing events. We also provide conditions under which the occupancy estimator provides correct estimates within a guaranteed probability. We test the estimator running experiments on a real testbed, in order to compare it with other occupancy estimation techniques and assess the value of having additional information sources.
Place, publisher, year, edition, pages
[Ebadat, Afrooz; Bottegal, Giulio; Wahlberg, Bo; Johansson, Karl H.] KTH Royal Inst Technol, Sch Elect Engn, Dept Automat Control, S-10044 Stockholm, Sweden. [Varagnolo, Damiano] Lulea Univ Innovat & Technol, Dept Comp Sci Elect & Space Engn, Div Signals & Syst, S-97187 Lulea, Sweden., 2015. Vol. 12, no 4, 1157-1168 p.
Deconvolution, occupancy estimation, regularization, system identification
IdentifiersURN: urn:nbn:se:kth:diva-176350DOI: 10.1109/TASE.2015.2471305ISI: 000362358500002ScopusID: 2-s2.0-84960796509OAI: oai:DiVA.org:kth-176350DiVA: diva2:867878
QC 201511062015-11-062015-11-032015-11-06Bibliographically approved