Related papers: Occupancy Detection in Room Using Sensor Data
Nowadays, many technological advances applied to the Internet of Things (IoT) make the introduction of innovative sensors aimed to deploy efficient wireless sensor networks possible. In order to improve the environment and people's lives,…
For effective integration of building operations into the evolving demand response programs of the power grid, real-time decisions concerning the use of building appliances for grid services must excel on multiple criteria, ranging from the…
A robot operating in a household makes observations of multiple objects as it moves around over the course of days or weeks. The objects may be moved by inhabitants, but not completely at random. The robot may be called upon later to…
Modern scientific advancements often contribute to the introduction and refinement of never-before-seen technologies. This can be quite the task for humans to maintain and monitor and as a result, our society has become reliant on machine…
Indoor localization has become an important issue for wireless sensor networks. This paper presents a zoning-based localization technique that uses WiFi signals and works efficiently in indoor environments. The targeted area is composed of…
Trajectory modelling had been the principal research area for understanding and anticipating human behaviour. Predicting the dynamic path by observing the agent and its surrounding environment are essential for applications such as…
This research proposes a machine learning-based attack detection model for power systems, specifically targeting smart grids. By utilizing data and logs collected from Phasor Measuring Devices (PMUs), the model aims to learn system…
Nowadays, the Internet of Things (IoT) is widely employed, and its usage is growing exponentially because it facilitates remote monitoring, predictive maintenance, and data-driven decision making, especially in the healthcare and industrial…
We present a data-driven car occupancy detection algorithm using ultra-wideband radar based on the ResNet architecture. The algorithm is trained on a dataset of channel impulse responses obtained from measurements at three different…
One of the primary goals in spectrum occupancy mapping is to create a system that is robust to assumptions about the number of sensors, occupancy threshold (in dBm), sensor noise, number of emitters and the propagation environment. We show…
This study investigates the integration of assistive therapeutic robotics, wearable sensors, and spatial sensors within an intelligent environment tailored for dementia care. The feasibility study aims to assess the collective impact of…
Mobile sensing has played a key role in providing digital solutions to aid with COVID-19 containment policies. These solutions include, among other efforts, enforcing social distancing and monitoring crowd movements in indoor spaces.…
This paper reports on a dynamic semantic mapping framework that incorporates 3D scene flow measurements into a closed-form Bayesian inference model. Existence of dynamic objects in the environment can cause artifacts and traces in current…
Building management systems tout numerous benefits, such as energy efficiency and occupant comfort but rely on vast amounts of data from various sensors. Advancements in machine learning algorithms make it possible to extract personal…
Energy consumption in residential and commercial buildings has increased dramatically worldwide in the last decade, due to the constant population and economic growth, the proliferation of electronic and consumer appliances. This has…
We develop a framework for analyzing multivariate time series using topological data analysis (TDA) methods. The proposed methodology involves converting the multivariate time series to point cloud data, calculating Wasserstein distances…
The growing adoption of IoT devices for healthcare has enabled researchers to build intelligence using all the data produced by these devices. Monitoring and diagnosing health have been the two most common scenarios where such devices have…
Humanoid robot technology is advancing rapidly, with manufacturers introducing diverse heterogeneous visual perception modules tailored to specific scenarios. Among various perception paradigms, occupancy-based representation has become…
Accurate perception of the surrounding environment is essential for safe autonomous driving. 3D occupancy prediction, which estimates detailed 3D structures of roads, buildings, and other objects, is particularly important for…
People spend a significant amount of time in indoor spaces (e.g., office buildings, subway systems, etc.) in their daily lives. Therefore, it is important to develop efficient indoor spatial query algorithms for supporting various…