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. See Fig. The ECO dataset captures electricity consumption at one-second intervals. In: ACS Sensors, Vol. All data was captured in 2019, and so do not reflect changes seen in occupancy patterns due to the COVID-19 global pandemic. See Fig. Seidel, R., Apitzsch, A. Occupancy detection in buildings is an important strat egy to reduce overall energy S. Y., Henze, G. & Sa rar, S. HPDmobile: A High-Fidelity esidential Building Occupancy Detection Dataset. SMOTE was used to counteract the dataset's class imbalance. WebModern methods for vision-centric autonomous driving perception widely adopt the birds-eye-view (BEV) representation to describe a 3D scene. http://creativecommons.org/licenses/by/4.0/, http://creativecommons.org/publicdomain/zero/1.0/, https://www.eia.gov/totalenergy/data/monthly/archive/00352104.pdf, https://www.eia.gov/consumption/residential/data/2015/, https://www.ecobee.com/wp-content/uploads/2017/01/DYD_Researcher-handbook_R7.pdf, https://arpa-e.energy.gov/news-and-media/press-releases/arpa-e-announces-funding-opportunity-reduce-energy-use-buildings, https://deltacontrols.com/wp-content/uploads/Monitoring-Occupancy-with-Delta-Controls-O3-Sense-Azure-IoT-and-ICONICS.pdf, https://www.st.com/resource/en/datasheet/vl53l1x.pdf, http://jmlr.org/papers/v12/pedregosa11a.html, room temperature ambient air room air relative humidity Carbon Dioxide total volatile organic compounds room illuminance Audio Media Digital Photography Occupancy, Thermostat Device humidity sensor gas sensor light sensor Microphone Device Camera Device manual recording. However, simple cameras are easily deceived by photos. The number that were verified to be occupied and verified to be vacant are given in n Occ and n Vac. 5 for a visual of the audio processing steps performed. The optimal cut-off threshold that was used to classify an image as occupied or vacant was found through cross-validation and was unique for each hub. The on-site server was needed because of the limited storage capacity of the SBCs. Weboccupancy-detection My attempt on the UCI Occupancy Detection dataset using various methods. We also quantified detections of barred owls ( Strix varia ), a congeneric competitor and important driver of spotted owl population declines. Lists of dark images are stored in CSV files, organized by hub and by day. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Values given are the number of files collected for that modality in that location, relative to the total number that could be collected in a day, averaged over all the days that are presented in the final dataset. Audio and image files are stored in further sub-folders organized by minute, with a maximum of 1,440minute folders in each day directory. Virtanen P, et al. Despite its better efficiency than voxel representation, it has difficulty describing the fine-grained 3D structure of a scene with a single plane. To generate the different image sizes, the 112112 images were either downsized using bilinear interpolation, or up-sized by padding with a white border, to generate the desired image size. Description Three data sets are submitted, for training and testing. The images shown are 112112 pixels. Install all the packages dependencies before trying to train and test the models. PeopleFinder (v2, GoVap), created by Shayaka 508 open source person images and annotations in multiple formats for training computer vision models. Days refers to the number of days of data that were released from the home, while % Occ refers to the percentage of time the home was occupied by at least one person (for the days released). The sensor is calibrated prior to shipment, and the readings are reported by the sensor with respect to the calibration coefficient that is stored in on-board memory. See Table1 for a summary of modalities captured and available. The collecting scenes of this dataset include indoor scenes and outdoor scenes (natural scenery, street view, square, etc.). GitHub is where people build software. This data diversity includes multiple scenes, 18 gestures, 5 shooting angels, multiple ages and multiple light conditions. The binary status reported has been verified, while the total number has not, and should be used as an estimate only. From these verified samples, we generated point estimates for: the probability of a truly occupied image being correctly identified (the sensitivity or true positive rate); the probability of a truly vacant image being correctly identified (the specificity or true negative rate); the probability of an image labeled as occupied being actually occupied (the positive predictive value or PPV); and the probability of an image labeled as vacant being actually vacant (the negative predictive value or NPV). The pandas development team. In order to confirm that markers of human presence were still detectable in the processed audio data, we trained and tested audio classifiers on pre-labeled subsets of the collected audio data, starting with both unprocessed WAV files (referred to as P0 files) and CSV files that had gone through the processing steps described under Data Processing (referred to as P1 files). Work fast with our official CLI. Occupancy detection of an office room from light, temperature, humidity and CO2 measurements. Since higher resolution did have significantly better performance, the ground truth labeling was performed on the larger sizes (112112), instead of the 3232 sizes that are released in the database. The server runs a separate Linux-based virtual machine (VM) for each sensor hub. WebThe publicly available dataset includes: grayscale images at 32-by-32 pixels, captured every second; audio files, which have undergone processing to remove personally identifiable / Chou, Chao Kai; Liu, Yen Liang; Chen, Yuan I. et al. To increase the utility of the images, zone-based labels are provided for the images. All data is collected with proper authorization with the person being collected, and customers can use it with confidence. Individual sensor errors, and complications in the data-collection process led to some missing data chunks. It includes a clear description of the data files. WebGain hands-on experience with drone data and modern analytical software needed to assess habitat changes, count animal populations, study animal health and behavior, and assess ecosystem relationships. Fisk, W. J., Faulkner, D. & Sullivan, D. P. Accuracy of CO2 sensors. In terms of device, binocular cameras of RGB and infrared channels were applied. Variable combinations have been tried as input features to the model in many different ways. WebOccupancy Detection Computer Science Dataset 0 Overview Discussion 2 Homepage http://archive.ics.uci.edu/ml/datasets/Occupancy+Detection+ Description Three data sets are submitted, for training and testing. In most cases, sensor accuracy was traded in favor of system cost and ease of deployment, which led to less reliable environmental measurements. 2, 28.02.2020, p. 296-302. Rice yield is closely related to the number and proportional area of rice panicles. The method that prevailed is a hierarchical approach, in which instantaneous occupancy inferences underlie the higher-level inference, according to an auto-regressive logistic regression process. Thus new pixel values are generated from linear combinations of the original values. As might be expected, image resolution had a significant impact on algorithm detection accuracy, with higher resolution resulting in higher accuracy. Example of the data records available for one home. STMicroelectronics. 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. Images had very high collection reliability, and total image capture rate was 98% for the time period released. Data for each home consists of audio, images, environmental modalities, and ground truth occupancy information, as well as lists of the dark images not included in the dataset. Additional benefits of occupancy detection in homes include enhanced occupant comfort, home security, and home health applications8. If nothing happens, download GitHub Desktop and try again. Volume 112, 15 January 2016, Pages 28-39. 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. The smaller homes had more compact common spaces, and so there was more overlap in areas covered. Are you sure you want to create this branch? Ground-truth occupancy was obtained from time stamped pictures that were taken every minute. In an autonomous vehicle setting, occupancy grid maps are especially useful for their ability to accurately represent the position of surrounding obstacles while being robust to discrepancies The model integrates traffic density, traffic velocity and duration of instantaneous congestion. Our best fusion algorithm is one which considers both concurrent sensor readings, as well as time-lagged occupancy predictions. The results show that while the predictive capabilities of the processed data are slightly lower than the raw counterpart, a simple model is still able to detect human presence most of the time. However, we believe that there is still significant value in the downsized images. An example of this is shown in Fig. We implemented multistate occupancy models to estimate probabilities of detection, species-level landscape use, and pair occupancy of spotted owls. This is a repository for data for the publication: Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models. Accuracy, precision, and range are as specified by the sensor product sheets. SciPy 1.0: Fundamental algorithms for scientific computing in Python. Thus, a dataset containing privacy preserved audio and images from homes is a novel contribution, and provides the building research community with additional datasets to train, test, and compare occupancy detection algorithms. Luis M. Candanedo, Vronique Feldheim. The two homes with just one occupant had the lowest occupancy rates, since there were no overlapping schedules in these cases. See Table3 for the average number of files captured by each hub. Sensors, clockwise from top right, are: camera, microphone, light, temperature/humidity, gas (CO2 and TVOC), and distance. binary classification (room occupancy) from Temperature,Humidity,Light and CO2. occupancy was obtained from time stamped pictures that were taken every minute. Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models. Luis M. Candanedo, Vronique Feldheim. 2021. Overall, audio had a collection rate of 87%, and environmental readings a rate of 89% for the time periods released. This dataset can be used to train and compare different machine learning, deep learning, and physical models for estimating occupancy at enclosed spaces. Points show the mean prediction accuracy of the algorithm on a roughly balanced set of labeled images from each home, while the error bars give the standard deviations of all observations for the home. Publishers note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. The data covers males and females (Chinese). At the end of the collection period, occupancy logs from the two methods (paper and digital) were reviewed, and any discrepancies or questionable entries were verified or reconciled with the occupants. 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). In addition to the environmental sensors mentioned, a distance sensor that uses time-of-flight technology was also included in the sensor hub. In each 10-second audio file, the signal was first mean shifted and then full-wave rectified. Description of the data columns(units etc). The homes tested consisted of stand-alone single family homes and apartments in both large and small complexes. Home layouts and sensor placements. The sensor was supposed to report distance of the nearest object up to 4m. The actual range it can report, however, is subject to an internal mode selection and is heavily impacted by ambient light levels. This meant that a Human Subject Research (HSR) plan was in place before any data taking began, and ensured that strict protocols were followed regarding both collection of the data and usage of it. Computing Occupancy grids with LiDAR data, is a popular strategy for environment representation. 2022-12-10 18:11:50.0, Euro NCAP announced that starting in 2022, it will start scoring child presence detection, a feature that detects that a child is left alone in a car and alerts the owner or emergency services to avoid death from heat stroke.. The final systems, each termed a Mobile Human Presence Detection system, or HPDmobile, are built upon Raspberry Pi single-board computers (referred to as SBCs for the remainder of this paper), which act as sensor hubs, and utilize inexpensive sensors and components marketed for hobby electronics. 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