occupancy detection dataset
Individual sensor errors, and complications in the data-collection process led to some missing data chunks. While the data acquisition system was initially configured to collect images at 336336 pixels, this was deemed to be significantly larger resolution than necessary for the ARPA-E project, and much larger than what would be publicly released. WebOccupancy-detection-data. (d) Average pixel brightness: 10. Since the data taking involved human subjects, approval from the federal Institutional Review Board (IRB) was obtained for all steps of the process. Training and testing sets were created by aggregating data from all hubs in a home to create larger, more diverse sets. Minimal processing on the environmental data was performed only to consolidate the readings, which were initially captured in minute-wise JSON files, and to establish a uniform sampling rate, as occasional errors in the data writing process caused timestamps to not always fall at exact 10-second increments. Using environmental sensors to collect data for detecting the occupancy state We created a synthetic dataset to investigate and benchmark machine learning approaches for the application in the passenger compartment regarding the challenges introduced in Section 1 and to overcome some of the shortcomings of common datasets as explained in Section 2. HHS Vulnerability Disclosure, Help Accuracy metrics for the zone-based image labels. Most data records are provided in compressed files organized by home and modality. With the exception of H2, the timestamps of these dark images were recorded in text files and included in the final dataset, so that dark images can be disambiguated from those that are missing due to system malfunction. The number of sensor hubs deployed in a home varied from four to six, depending on the size of the living space. Learn more. Volume 112, 15 January 2016, Pages 28-39. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Most sensors use the I2C communication protocol, which allows the hub to sample from multiple sensor hubs simultaneously. Multi-race Driver Behavior Collection Data, 50 Types of Dynamic Gesture Recognition Data, If you need data services, please feel free to contact us at. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. The TVOC and CO2 sensor utilizes a metal oxide gas sensor, and has on-board calibration, which it performs on start-up and at regular intervals, reporting eCO2 and TVOC against the known baselines (which are also recorded by the system). In the last two decades, several authors have proposed different methods to render the sensed information into the grids, seeking to obtain computational efficiency or accurate environment modeling. In 2020, residential energy consumption accounted for 22% of the 98 PJ consumed through end-use sectors (primary energy use plus electricity purchased from the electric power sector) in the United States1, about 50% of which can be attributed to heating, ventilation, and air conditioning (HVAC) use2. Studies using PIR sensors and smart thermostats show that by accounting for occupancy use in HVAC operations, residential energy use can be reduced by 1547%35. Radar provides depth perception through soft materials such as blankets and other similar coverings that cover children. 0-No chances of room occupancy Inspiration WebOccupancy detection of an office room from light, temperature, humidity and CO2 measurements using TPOT (A Python tool that automatically creates and optimizes machine Some homes had higher instances of false positives involving pets (see Fig. See Table1 for a summary of modalities captured and available. Cite this APA Author BIBTEX Harvard Standard RIS Vancouver To increase the utility of the images, zone-based labels are provided for the images. Timestamps were simply rounded to the nearest 10-second increment, and any duplicates resulting from the process were dropped. The Filetype shows the top-level compressed files associated with this modality, while Example sub-folder or filename highlights one possible route to a base-level data record within that folder. Summary of the completeness of data collected in each home. Description Three data sets are submitted, for training and testing. There are no placeholders in the dataset for images or audio files that were not captured due to system malfunction, and so the total number of sub-folders and files varies for each day. In addition to the environmental sensors mentioned, a distance sensor that uses time-of-flight technology was also included in the sensor hub. Currently, Tier1 suppliers in the market generally add infrared optical components to supplement the shortcomings of cameras. Two independent systems were built so data could be captured from two homes simultaneously. like this: from detection import utils Then you can call collate_fn However, we are confident that the processing techniques applied to these modalities preserve the salient features of human presence. Caleb Sangogboye, F., Jia, R., Hong, T., Spanos, C. & Baun Kjrgaard, M. A framework for privacy-preserving data publishing with enhanced utility for cyber-physical systems. The images shown are 112112 pixels. Images that had an average value of less than 10 were deemed dark and not transferred off of the server. FOIA Additional key requirements of the system were that it (3) have the ability to collect data concurrently from multiple locations inside a house, (4) be inexpensive, and (5) operate independently from residential WiFi networks. WebData Descriptor occupancy detection dataset Margarite Jacoby 1 , Sin Yong Tan 2, Gregor Henze1,3,4 & Soumik Sarkar 2. Based on this, it is clear that images with an average pixel value below 10 would provide little utility in inferential tasks and can safely be ignored. 2019. If nothing happens, download Xcode and try again. (a) Raw waveform sampled at 8kHz. It mainly includes radar-related multi-mode detection, segmentation, tracking, freespace space detection papers, datasets, projects, related docs Radar Occupancy Prediction With Lidar Supervision While Preserving Long-Range Sensing and Penetrating Capabilities: freespace generation: lidar & radar: pandas-dev/pandas: Pandas. False positive cases, (i.e., when the classifier thinks someone is in the image but the ground truth says the home is vacant) may represent a mislabeled point. The climate in Boulder is temperate, with an average of 54cm of annual precipitation, in the form of rain in the summer and snow in the winter. Luis M. Candanedo, Vronique Feldheim. Energy and Buildings. If nothing happens, download GitHub Desktop and try again. to use Codespaces. has developed series of OMS and DMS training datasets, covering a variety of application scenarios, such as driver & passenger behavior recognition, gesture control, facial recognition and etc. Scoring >98% with a Random Forest and a Deep Feed-forward Neural Network Because the environmental readings are not considered privacy invading, processing them to remove PII was not necessary. An Artificial Neural Network (ANN) was used in this article to detect room occupancy from sensor data using a simple deep learning model. In terms of device, binocular cameras of RGB and infrared channels were applied. The modalities as initially captured were: Monochromatic images at a resolution of 336336 pixels; 10-second 18-bit audio files recorded with a sampling frequency of 8kHz; indoor temperature readings in C; indoor relative humidity (rH) readings in %; indoor CO2 equivalent (eCO2) readings in part-per-million (ppm); indoor total volatile organic compounds (TVOC) readings in parts-per-billion (ppb); and light levels in illuminance (lux). This operated through an if-this-then-that (IFTTT) software application that was installed on a users cellular phone. See Fig. Please read the commented lines in the model development file. Thank you! Luis M. Candanedo, Vronique Feldheim. Leave your e-mail, we will get in touch with you soon. Sensors, clockwise from top right, are: camera, microphone, light, temperature/humidity, gas (CO2 and TVOC), and distance. We also quantified detections of barred owls ( Strix varia ), a congeneric competitor and important driver of spotted owl population declines. Contact us if you WebAbout Dataset Data Set Information: The experimental testbed for occupancy estimation was deployed in a 6m 4.6m room. sign in Verification of the ground truth was performed by using the image detection algorithms developed by the team. This process is irreversible, and so the original details on the images are unrecoverable. Rice yield is closely related to the number and proportional area of rice panicles. An official website of the United States government. How to Build a Occupancy Detection Dataset? Also reported are the point estimates for: True positive rate (TPR); True negative rate (TNR); Positive predictive value (PPV); and Negative predictive value (NPV). The fact that all homes had cameras facing the main entrance of the home made it simple to correct these cases after they were identified. Hobson BW, Lowcay D, Gunay HB, Ashouri A, Newsham GR. This is most likely due to the relative homogeneity of the test subjects, and the fact that many were graduate students with atypical schedules, at least one of whom worked from home exclusively. The data we have collected builds on the UCI dataset by capturing the same environmental modalities, while also capturing privacy preserved images and audio. Implicit sensing of building occupancy count with information and communication technology data sets. Section 5 discusses the efficiency of detectors, the pros and cons of using a thermal camera for parking occupancy detection. In addition to the digital record, each home also had a paper backup that the occupants were required to sign-in and out of when they entered or exited the premises. Volume 112, 15 January 2016, Pages 28-39. In total, three datasets were used: one for training and two for testing the models in open and closed-door occupancy scenarios. Webpatient bed occupancy to total inpatient bed occupancy, the proportion of ICU patients with APACHE II score 15, and the microbiology detection rate before antibiotic use. The sensors are connected to the SBC via a custom designed printed circuit board (PCB), and the SBC provides 3.3 Vdc power to all sensors. The ANN model's performance was evaluated using accuracy, f1-score, precision, and recall. Ground-truth occupancy was The authors wish the thank the following people: Cory Mosiman, for his instrumental role in getting the data acquisition system set up; Hannah Blake and Christina Turley, for their help with the data collection procedures; Jasmine Garland, for helping to develop the labeled datasets used in technical validation; the occupants of the six monitored homes, for letting us invade their lives. To aid in retrieval of images from the on-site servers and later storage, the images were reduced to 112112 pixels and the brightness of each image was calculated, as defined by the average pixel value. Readers might be curious as to the sensor fusion algorithm that was created using the data collected by the HPDmobile systems. privacy policy. In light of recently introduced systems, such as Delta Controls O3 sensor hub24, a custom designed data acquisition system may not be necessary today. Area monitored is the estimated percent of the total home area that was covered by the sensors. See Table4 for classification performance on the two file types. E.g., the first hub in the red system is called RS1 while the fifth hub in the black system is called BS5. 1a for a diagram of the hardware and network connections. Thrsh gives the hub specific cut-off threshold that was used to classify the image as occupied or vacant, based on the output from the YOLOv5 algorithm. 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