Related papers: PoHAR: Understanding Hyperlocal Human Activities w…
Plausibility of data from networks of low-cost measurement devices is a growing and important contentious issue. Informal networks of low-cost devices have particularly come to prominence for air quality monitoring. The contentious point is…
This paper presents a comprehensive dataset intended to evaluate passive Human Activity Recognition (HAR) and localization techniques with measurements obtained from synchronized Radio-Frequency (RF) devices and vision-based sensors. The…
Recent years have witnessed the rapid development of human activity recognition (HAR) based on wearable sensor data. One can find many practical applications in this area, especially in the field of health care. Many machine learning…
Much of the energy consumption in buildings is due to HVAC systems, which has motivated several recent studies on making these systems more energy- efficient. Occupancy and activity are two important aspects, which need to be correctly…
People are increasingly concerned with understanding their personal environment, including possible exposure to harmful air pollutants. In order to make informed decisions on their day-to-day activities, they are interested in real-time…
As elderly population grows, social and health care begin to face validation challenges, in-home monitoring is becoming a focus for professionals in the field. Governments urgently need to improve the quality of healthcare services at lower…
Global ambient air pollution, a transboundary challenge, is typically addressed through interventions relying on data from spatially sparse and heterogeneously placed monitoring stations. These stations often encounter temporal data gaps…
Current air pollution monitoring systems are bulky and expensive resulting in a very sparse deployment. In addition, the data from these monitoring stations may not be easily accessible. This paper focuses on studying the dense deployment…
The preservation of cultural heritage faces growing challenges from climate change, tourism pressure, and limited conservation resources. Existing monitoring solutions are often cost-prohibitive, proprietary, and inflexible, leaving many…
Public space utilization is crucial for urban developers to understand how efficient a place is being occupied in order to improve existing or future infrastructures. In a smart cities approach, implementing public space monitoring with…
In this article we present SHARP, an original approach for obtaining human activity recognition (HAR) through the use of commercial IEEE 802.11 (Wi-Fi) devices. SHARP grants the possibility to discern the activities of different persons,…
Human Activity Recognition (HAR) is one of the key applications of health monitoring that requires continuous use of wearable devices to track daily activities. This paper proposes an Adaptive CNN for energy-efficient HAR (AHAR) suitable…
Continuous detection of human activities and presence is essential for developing a pervasive interactive smart space. Existing literature lacks robust wireless sensing mechanisms capable of continuously monitoring multiple users'…
Multisensor fusion of air pollutant data in smart buildings remains an important input to address the well-being and comfort perceived by their inhabitants. An integrated sensing system is part of a smart building where real-time indoor air…
We designed and performed a participatory sensing initiative to explore the reliability and effectiveness of a distributed network of citizen-operated smartphones in evaluating the impact of environmental noise in residential areas. We…
Cost-effective sensors are capable of real-time capturing a variety of air quality-related modalities from different pollutant concentrations to indoor/outdoor humidity and temperature. Machine learning (ML) models are capable of performing…
Many real-world scenarios for massive machine-type communication involve sensors monitoring a physical phenomenon. As a consequence, the activity pattern of these sensors will be correlated. In this letter, we study how the correlation of…
We introduce the holographic air-quality monitor (HAM) system, uniquely tailored for monitoring large particulate matter (PM) over 10 um in diameter, i.e., particles critical for disease transmission and public health but overlooked by most…
Low-cost miniaturised sensors offer significant advantage to monitor the environment in real-time and accurately. The area of air quality monitoring has attracted much attention in recent years because of the increasing impacts on the…
Automatic recognition of human activities from time-series sensor data (referred to as HAR) is a growing area of research in ubiquitous computing. Most recent research in the field adopts supervised deep learning paradigms to automate…