Direct Manufacturer Enhancing thermal comfort and sustainability in building energy
In this work, we propose a novel edge machine learning-based smart controller for air conditioners to maintain user-preferred thermal comfort levels while minimizing energy consumption.
Direct Manufacturer Smart Building Management System based on Digital Twin: A Case
As urban landscapes increasingly transform into smart cities, there is an increasing emphasis on smart buildings for sustainable and efficient management of resources. This evolution necessitates
Direct Manufacturer Smart Building: Decision Making Architecture for
Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks,
Direct Manufacturer Thermal Resilience of Buildings and Communities: A
This review provides actionable insights and identifies future research needs for enhancing resilience through tailored metrics for stakeholders during
Direct Manufacturer Monitoring and analytics to measure heat resilience of buildings and
Designing buildings to prevent indoor overheating requires the definition of accurate procedures to measure the passive survivability of buildings and support retrofitting. This research
Direct Manufacturer Maximizing Energy Efficiency with Temperature
Learn how temperature monitoring can help building owners optimize energy efficiency in smart buildings. Discover best practices and benefits of
Direct Manufacturer Enhancing thermal comfort and sustainability in building energy
Occupants often struggle with extreme temperatures, leading to increased energy consumption due to excessive use of air conditioners and heaters. In this work, we propose a novel
Direct Manufacturer Assessing energy saving potentials of office buildings based on
The aim of this study is to investigate the interaction between occupants'' thermal sensation and adaptive behavior in office buildings. Such understanding can provide detailed
Direct Manufacturer Fully data-driven and modular building thermal control with physically
By leveraging a modular design, a thermal controller trained on a source building can be effectively transferred to new buildings. The first module, a reinforcement learning agent is thought to
Direct Manufacturer An IoT-based Thermal Model Learning Framework for Smart Buildings
This study shows the validity of the proposed IoT-based thermal model learning framework, and offers a pragmatic solution for providing reliable thermal models to future smart building climate
Direct Manufacturer Deep Transfer Learning for Thermal Dynamics Modeling in Smart
While a data-driven model can be adopted easily to describe the thermal dynamics for a specific building in a time interval, there exists difficulty that needs to be addressed on transferring established
Direct Manufacturer Energy-Efficient Thermal Comfort Control in Smart Buildings
The heating, ventilation, and air conditioning (HVAC) systems in commercial buildings consume 20%-40% of the USA''s total building energy consumption. This paper proposes a novel energy-efficient
Direct Manufacturer Digital twin based deep learning framework for personalized thermal
To overcome these limitations, we introduce a Digital Twin-driven framework integrated with an advanced attention-based Long Short-Term Memory (LSTM) model specifically tailored for
Direct Manufacturer Energy-Efficient Thermal Comfort Control in Smart Buildings via
Different from previous works, we propose a learning-based framework for joint energy optimization and thermal comfort control in smart buildings. We first design a deep neural network method with
Direct Manufacturer Demystifying Thermal Comfort in Smart Buildings: An Interpretable
Thermal comfort is a key consideration in smart buildings and a number of comfort models are available nowadays to evaluate the comfort level of occupants. However, the models are often
Direct Manufacturer An IoT-Based Thermal Model Learning Framework for Smart Buildings
In this article, taking advantage of IoT technologies, a plug-and-play learning framework is proposed to automatically identify the thermal model of each thermal zone in a building without
Direct Manufacturer Model Predictive Control for Smart Buildings: Applications and
The integration of advanced control strategies into building energy management systems (BEMS) is essential for achieving energy efficiency and sustaining thermal comfort. Model predictive
Direct Manufacturer Human-in-the-Loop Thermal Management for Smart Buildings
While the primary purpose of most buildings is to provide a safe and comfortable environment for its occupants, most of the current studies and solutions developed for building
Direct Manufacturer Temperature and humidity transmitters: The backbone of smart buildings
Explore how temperature and humidity transmitters enhance smart building efficiency, focusing on HVAC optimization, IoT-driven savings, and real-time data utilization. Discover their impact on
Direct Manufacturer A Comprehensive Review of Sensor-Based Smart
Intending to design an effective smart building monitoring system, this research paper explores and compares various solutions for measuring building
Direct Manufacturer (PDF) A Machine Learning-Based Temperature Control
A Machine Learning-Based T emperature Control and Security Protection for Smart Buildings Mostafa Zaman 1, Maher Al Islam 1, Nasibeh
Direct Manufacturer Energy-efficient heating control for smart buildings with deep
Therefore, it is necessary to design energy-efficient controllers that can improvise occupant thermal comfort (deviation from setpoint temperature) while reducing energy consumption.
Direct Manufacturer Thermal Tracking: Diagnose Indoor Wall or Ceiling Ghosting Stains
Indoor stains in buildings traced to black or dark thermal tracking or ghosting lines: Building Air Leaks & Heat Loss Points. This article describes & diagnoses the cause of various interior wall and ceiling
Direct Manufacturer Data-driven identification of a thermal network in multi-zone buildi
ec-essary for their optimal control and application in demand response. The thermal response of a building around an operating point can be modeled using a network of inter- onnected resistors with