2017 Progress Report: Sensible Home: Micro-environmental control through wearable personal sensorsEPA Grant Number: SU836940
Title: Sensible Home: Micro-environmental control through wearable personal sensors
Investigators: Wang, Julian , Fan, Howard
Institution: University of Cincinnati
EPA Project Officer: Callan, Richard
Project Period: February 1, 2017 through January 31, 2019 (Extended to January 31, 2022)
Project Period Covered by this Report: February 1, 2017 through January 31,2018
Project Amount: $75,000
RFA: P3 Awards: A National Student Design Competition for Sustainability Focusing on People, Prosperity and the Planet - Phase 2 (2016) Recipients Lists
Research Category: P3 Challenge Area - Chemical Safety , Sustainable and Healthy Communities , P3 Awards
Our long-term research goal is to bring the human-in-the-loop of residential building controls using personal wearable sensors and lead to new advances in building energy efficiency and indoor comfort. As a step toward this, this P3 Phase II project targets the senior populations who were found to have significant demands regarding indoor comfort and health, develops a reliable integrative comfort model upon wearable sensor data, and determines the methods taking energy saving considerations into account. The experimental testing of the developed prototype consisting of a personal wearable module and a computing module connected to a laptop is planned for a senior living residence, in collaboration with a local non-profit continuing care retirement community. Built upon the theoretical demonstration in Phase I, the ultimate goal of this Phase II project is to improve and verify our concept and prepare it for implementation, in an effort to benefit individual indoor comfort (people), promote economic growth in smart buildings and healthcare (prosperity), and build energy efficiency (the planet).
1) Wearable module development
We completed an initial design of the personal wearable module. The structural layout and sensors of the personal wearable module are shown in Figure 1. As shown in the structural layout in this figure, the designed wearable mode is the clipped type consisting of two parts monitoring both inside and outside conditions. In such a way, all necessary micro-environmental parameters
and biomarkers can be retrieved. The microcontroller board used for this module t is the Arduino Uno R3. The selected sensors and components are listed in Table 1, which also includes the main sensor information such as its function, accuracy, dimensions, etc. We have calibrated individual sensor in this list and also assembled the sensors on the platform.
The challenge to the research team was to monitor the clothing insulation, which is one of the important variables to yield comfort index, using simplified sensing and measuring method as it normally needs a costly and complex thermal flux sensor. In this project, we used low-cost temperature sensors. The inside element documents the skin temperature (Tint), while the outside portion records the air’s ambient temperature (Text). From the known area (A) of the surface touching the sensors and the known material insulation (R), we could calculate the clothing insulation upon the steady heat transfer in which the rate of heat transfer remains constant.
In addition, in order to make all sensors and platforms to be packed in a whole, we carefully designed the shapes and layouts of the module and will use 3D printer to fabricate this module, which will be done in the next phase.
2) Method identification for individualized indoor comfort model
In this phase, we also identified the methods to develop the individualized indoor comfort model. We decided to use a two-stage procedure to develop the individualized indoor comfort model that accounts for both information-based individualization and rule-based individualization. The first stage is offline stage, where we construct a gradient boosting decision trees model to predict thermal comfort level based on environmental status, sensor data and personal information. The second stage is the online calibration stage, where repeated measurements on each user is collected from sensors and true users’ responses. Both the model development and the alerting system development will be performed on the UC campus.
3) Occupant-centered building control energy use and indoor comfort comparison
We performed comprehensive building energy and comfort simulations based on comfort-behavior driven building control loop and then compare it to the simulations based on fixed control schedule, which determined if there was improvement in energy and comfort levels. We used 18 residential units for our simulation comparison. In the context of source energy, the model with the behavior-driven controls used 6.6% less energy compared to the model with the fixed schedule thermostat controls. On the other side, the indoor comfort level was greatly improved by using the micro-environment control. The following figure presents the Predicted Mean Vote (PMV) comparison between two control methods. The PMV refers to a thermal scale
4) User study preparation
To prepare the user study, we have retrofitted a lab space which has a central computer-based environmental control functions to control temperature, humidity, lights, and fans. The renovation is still under the process and should be completed in June. Meanwhile, the Institutional Review Board (IRB) application of the topic of “User Indoor Comfort Study Using Personal Sensors” has been approved by the University of Cincinnati IRB Office on November 20, 2017. The IRB approval materials have been submitted to the Project Office.
Journal Articles on this Report : 2 Displayed | Download in RIS Format
|Other project views:||All 16 publications||6 publications in selected types||All 6 journal articles|
||Li J, Qi M, Wang J. Designing for microclimatic comfort and health:A rapid prediction model of environmental conditions. Nano Life 2018;8(2):17-32.||
|| Duan Q, Wang J. Thermal Conditions Controlled by Thermostats:An Occupational Comfort and Well-being Perspective. Civil Engineering and Architecture 2017;5(5). .