相关论文: Beyond Control: Enabling Smart Thermostats For Lea…
Predictive maintenance is used in industrial applications to increase machine availability and optimize cost related to unplanned maintenance. In most cases, predictive maintenance applications use output from sensors, recording physical…
We introduce two types of thermodynamic refrigeration cycles obtained through modification of the Otto cycle refrigerator by a generalized measurement channel. These refrigerators are corresponding to the activation of the measurement-based…
This paper introduces a feedback-based temperature controller design for intelligent regulation of food internal temperature inside of standard convection ovens. Typical convection ovens employ an open-loop control system that requires a…
An inventory management system for the freezer powered by photovoltaic panels was developed in this study. It aims to promote energy efficiency and the responsible use of food. Its sensor network is an Arduino-based wireless network of…
Active thermal control is crucial in achieving the required accuracy and throughput in many industrial applications, e.g., in the medical industry, high-power lighting industry, and semiconductor industry. Thermoelectric Modules (TEMs) can…
This research presents a smart urinary health monitoring system incorporating a coplanar waveguide (CPW)-fed slot-loop antenna biosensor designed to analyse various urine samples. The antenna demonstrates distinct resonant frequency shifts…
One key requirement for effective supply chain management is the quality of its inventory management. Various inventory management methods are typically employed for different types of products based on their demand patterns, product…
In the digitization of energy systems, sensors and smart meters are increasingly being used to monitor production, operation and demand. Detection of anomalies based on smart meter data is crucial to identify potential risks and unusual…
In smart grid, malicious customers may compromise their smart meters (SMs) to report false readings to achieve financial gains illegally. Reporting false readings not only causes hefty financial losses to the utility but may also degrade…
It is envisioned that building systems will become active participants in the smart grid operation by controlling their energy consumption to optimize complex criteria beyond ensuring local end-use comfort satisfaction. A forecast of the…
The technologies used in smart homes have recently improved to learn the user preferences from feedback in order to enhance the user convenience and quality of experience. Most smart homes learn a uniform model to represent the thermal…
Precise temperature monitoring -- to the level of a few milli-Kelvin -- is essential for the operation of large-scale cryostats requiring a recirculation system. In particular, the performance of Liquid Argon Time Projection Chambers --…
With the press of global climate change, extreme weather and sudden weather changes are becoming increasingly common. To maintain a comfortable indoor environment and minimize the contribution of the building to climate change as much as…
Temperature sensing and control systems are widely used in the closed-loop control of critical processes such as maintaining the thermal stability of patients, or in alarm systems for detecting temperature-related hazards. However, the…
Prediabetes is a common health condition that often goes undetected until it progresses to type 2 diabetes. Early identification of prediabetes is essential for timely intervention and prevention of complications. This research explores the…
We introduce NeedForHeat DataGear: an open hardware and open software data collection system designed to accelerate the residential heating transition. NeedForHeat DataGear collects time series monitoring data in homes that have not yet…
Over the past decade, millions of smart meters have been installed by electricity suppliers worldwide, allowing them to collect a large amount of electricity consumption data, albeit sampled at a low frequency (one point every 30min). One…
Deep learning models, particularly Long Short-Term Memory (LSTM) networks, are widely used in time series forecasting due to their ability to capture complex temporal dependencies. However, evaluation integrity is often compromised by data…
In the residential sector, electric water heaters are appliances with a relatively high power consumption and a significant thermal inertia, which is particularly suitable for Demand Response schemes. The success of efficient DR schemes via…
Detectors in particle physics, particularly when including cryogenic components, are often enclosed in vessels that do not provide any physical or visual access to the detectors themselves after installation. However, it can be desirable…