scholarly journals Development of CNN-based visual recognition air conditioner for smart buildings

2020 ◽  
Vol 25 ◽  
pp. 361-373
Author(s):  
Qian Huang ◽  
Kangli Hao
Keyword(s):  
Visual Recognition ◽  
Detection Methods ◽  
Air Conditioner ◽  
Smart Buildings ◽  
Existing Building ◽  
Air Conditioners ◽  
Occupancy Detection ◽  
Expected Performance ◽  
Carbon Dioxide Sensors ◽  
Building Occupancy

Demand-driven heating, ventilation, and air conditioning (HVAC) operations have become very attractive in energy-efficient smart buildings. Demand-oriented HVAC control largely relies on accurate detection of building occupancy levels and locations. So far, existing building occupancy detection methods have their disadvantages, and cannot fully meet the expected performance. To address this challenge, this paper proposes a visual recognition method based on convolutional neural networks (CNN), which can intelligently interpret visual contents of surveillance cameras to identify the number of occupants and their locations in buildings. The proposed study can detect the quantity, distance, and angle of indoor human users, which is essential for controlling air-conditioners to adjust the direction and speed of air blow. Compared with the state of the art, the proposed method successfully fulfills the function of building occupant counting, which cannot be realized when using PIR, sound, and carbon dioxide sensors. Our method also achieves higher accuracy in detecting moving or stationary human bodies and can filter out false detections (such as animal pets or moving curtains) that are existed in previous solutions. The proposed idea has been implemented and collaboratively tested with air conditioners in an office environment. The experimental results verify the validity and benefits of our proposed idea.

scholarly journals Optimal Air Conditioner Placement Using a Simple Thermal Environment Analysis Method for Continuous Large Spaces with Predominant Advection

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4663
Author(s):  
Tatsuhiro Yamamoto ◽  
Akihito Ozaki ◽  
Myonghyang Lee
Keyword(s):  
Air Conditioning ◽  
Thermal Environment ◽  
Fluid Dynamic ◽  
Optimal Placement ◽  
Air Conditioner ◽  
Analysis Method ◽  
Computational Fluid Dynamic Analysis ◽  
Environment Analysis ◽  
Air Conditioners ◽  
Energy Simulations

The number of houses with large, continuous spaces has increased recently. With improvements in insulation performance, it has become possible to efficiently air condition such spaces using a single air conditioner. However, the air conditioning efficiency depends on the placement of the air conditioner. The only way to determine the optimal placement of such air conditioners is to conduct an experiment or use computational fluid dynamic analysis. However, because the analysis is performed over a limited period, it is difficult to consider non-stationarity effects without using an energy simulation. Therefore, in this study, energy simulations and computational fluid dynamics analyses were coupled to develop a thermal environment analysis method that considers non-stationarity effects, and various air conditioner arrangements were investigated to demonstrate the applicability of the proposed method. The accuracy verification results generally followed the experimental results. A case study was conducted using the calculated boundary conditions, and the results showed that the placement of two air conditioners in the target experimental house could provide sufficient air conditioning during both winter and summer. Our results suggest that this method can be used to conduct preliminary studies if the necessary data are available during design or if an experimental house is used.

Solar Heat Underground Storage Based Air Conditioning Vis-à-Vis Conventional HVAC Experimental Validation

2017 ◽  
Vol 140 (1) ◽  
Author(s):  
Carlos R. de Nardin ◽  
Felipe T. Fernandes ◽  
Adriano J. Longo ◽  
Luciano P. Lima ◽  
Felix A. Farret ◽  
...  
Keyword(s):  
Air Conditioning ◽  
Heat Pumps ◽  
Conventional Heating ◽  
Management Technique ◽  
Air Conditioner ◽  
Heat Management ◽  
Air Conditioners ◽  
Solar Heat ◽  
Reduction Of Energy Consumption ◽  
The One

This paper presents a comparison of air conditioners using the conventional heating, ventilation, and air conditioning heat pumps and the one using solar heat stored underground, also known as shallow geothermal air conditioning. The proposed air conditioner with solar heat stored underground reunites practical data from an implementation of the heuristic perturb-and-observe (P&O) control and a heat management technique. The aim is to find out the best possible heat exchange between the room ambient and the underground soil heat to reduce its overall consumption without any heat pump. Comparative tests were conducted in two similar rooms, each one equipped with one of the two types of air conditioning. The room temperature with the conventional air conditioning was maintained as close as possible to the temperature of the test room with shallow geothermal conditioning to allow an acceptable data validation. The experiments made both in the winter of 2014 and in the summer of 2015 in Santa Maria, South Brazil, demonstrated that the conventional air conditioner consumed 19.08 kWh and the shallow geothermal conditioner (SGC) consumed only 4.65 kWh, therefore, representing a reduction of energy consumption of approximately 75%.

Performance evaluation and design considerations for a split air-conditioner with built-in thermal energy storage

2018 ◽  
Vol 40 (5) ◽  
pp. 560-575
Author(s):  
Jehanzeb Ahmad ◽  
M Najam Ul Islam ◽  
Jawwad Sabir
Keyword(s):  
Energy Storage ◽  
Phase Change ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Phase Change Materials ◽  
Low Cost ◽  
Hvac Systems ◽  
Air Conditioner ◽  
Widespread Application ◽  
Air Conditioners

The benefits of thermal energy storage using phase change materials are well documented in the literature. Despite all the potential benefits of thermal energy storage, its commercial and widespread application remains limited. This is due to the high initial cost of phase change materials, extensive rework required in buildings, major modifications in HVAC systems, and the potential for leakage, fire and toxicity hazards. There is a strong need for a simple thermal energy storage solution which can be adopted by large number of consumers. Ductless split air-conditioners are portable, low cost, efficient and account for 70% of all air-conditioning systems sold worldwide each year. The present research provides a novel and low cost solution that incorporates thermal energy storage in these air conditioners, allowing them to run without electricity for 3 h. The paper deals with the detailed design aspects and engineering challenges that arise when incorporating thermal energy storage in these small units. A prototype air-conditioner with in-built thermal energy storage was developed, and all performance parameters presented have been validated through data obtained from the prototype. Our results indicate that thermal energy storage can be incorporated in split units in low cost and with minimal drop in overall energy efficiency of the system. Practical application: Incorporating thermal energy storage in split air-conditioners which enables them to run without grid for many hours has immense practical applications. Since around 50% power in any building is consumed by HVAC systems, being able to provide cooling during peak hours without using grid can significantly reduce load on the grid without compromising user comfort. For developing countries where load shedding is frequent, the users can run these air-conditioners without the use of generators or batteries thus saving costs and the environment.

scholarly journals KINERJA TERMAL SELUBUNG GEDUNG KULIAH KOTA BANDAR LAMPUNG ITERA

2019 ◽  
Vol 3 (3) ◽  
pp. 267
Author(s):  
Andi Asrul Sani ◽  
Adelia Enjelina Matondang ◽  
Guruh Kristiadi Kurniawan ◽  
Anggi Mardiyanto
Keyword(s):  
Heat Transfer ◽  
Energy Consumption ◽  
Building Energy ◽  
Air Conditioner ◽  
Tropical Country ◽  
Air Conditioners ◽  
Natural Lighting ◽  
Thermal Transfer ◽  
Institute Of Technology ◽  
Window Area

Abstract: The use of glass material should consider the comfort of space in the building. Field of glass is needed as natural lighting and visual facilities between the occupants and the surrounding environment. Its function as natural lighting is often accompanied by an increase in temperature in buildings, considering that Indonesia is a tropical country. Building temperatures that increase due to incoming sunlight can cause discomfort to building occupants. Such conditions make building occupants use air conditioner (AC). The use of air conditioners can increase the value of building energy consumption. For this reason, research on the value of heat transfer in buildings or the value of OTTV (Overall Thermal Transfer Value). OTTV value calculation is done by manual calculation. Bandar Lampung City lecture building at the Sumatra Institute of Technology was chosen as the object of this study. From the results of the study found that the value of heat transfer of a building or OTTV (Overall Thermal Transfer Value) is influenced by the factor of the ratio of the window area to the facade or WWR (Window Wall Ratio) and the shading factor (Shading Coefficient).(Keywords: Keyword: energy consumption, building energy, glass. Abstract: Penggunaan material kaca semestinya mempertimbangkan kenyamanan ruang dalam bangunan. Bidang kaca diperlukan sebagai pencahayaan alami dan sarana visual antara penghuni dan lingkungan sekitar. Fungsinya sebagai pencahayaan alami seringkali disertai dengan peningkatan temperatur pada bangunan, mengingat Indonesia merupakan negara yang beriklim tropis. Temperatur bangunan yang meningkat akibat dari radiasi sinar matahari yang masuk dapat menyebabkan ketidaknyamanan bagi penghuni bangunan. Kondisi seperti itu membuat penghuni bangunan menggunakan air conditioner (AC). Penggunaan air conditioner tersebut dapat meningkatkan nilai konsumsi energi bangunan. Untuk  itu dilakukan penelitian mengenai nilai perpindahan panas dalam bangunan atau nilai OTTV (Overall Thermal Transfer Value). Penghitungan nilai OTTV dilakukan dengan penghitungan manual. Gedung kuliah Kota Bandar Lampung di Institut Teknologi Sumatera di pilih sebagai objek dalam penelitian ini. Dari hasil penelitian ditemukan bahwa nilai perpindahan panas suatu bangunan atau OTTV (Overall Thermal Transfer Value) dipengaruhi oleh faktor nilai perbandingan luas jendela terhadap bidang fasad atau WWR (Window Wall Ratio) dan faktor pembayangan (Shading Coefficient).Kata kunci : konsumsi energi, energi bangunan, kaca.

Psycho-physiological evaluations of low-level impulsive sounds produced by air conditioners

2021 ◽  
Vol 263 (5) ◽  
pp. 1186-1193
Author(s):  
Yoshiharu Soeta ◽  
Ei Onogawa
Keyword(s):  
Sound Pressure ◽  
Living Room ◽  
Air Conditioner ◽  
Regression Analyses ◽  
Noise Sources ◽  
Air Conditioners ◽  
Low Level ◽  
Subjective Loudness ◽  
Long Time

Air conditioners are widely used in buildings to maintain thermal comfort for long time. Air conditioners produce sounds during operation, and air conditioners are regarded as one of the main noise sources in buildings. Most sounds produced by the air conditioner do not fluctuate over time and sound quality of the steady sounds produced by the air conditioner have been evaluated. However, air conditioners sometimes produce low-level and impulsive sounds. Customers criticizes such sounds are annoying when they sleep and they spend time quietly in the living room. The aim of this study was to determine the factors that significantly influence the psycho-physiological response to the low-level impulsive sounds produced by air conditioners. We assessed the A-weighted equivalent continuous sound pressure level (LAeq) and factors extracted from the autocorrelation function (ACF). Subjective loudness, sharpness, annoyance, and electroencephalography (EEG) were evaluated. Multiple regression analyses were performed using a linear combination of LAeq, the ACF factors, and their standard deviations. The results indicated that LAeq, the delay time of the first maximum peak, the width of the first decay of the ACF, and the magnitude and width of the IACF could predict psycho-physiological responses to air conditioner sounds.

Low-Resolution IR Sensor-based Occupancy Detection Scheme for Smart Buildings

2021 ◽  
Author(s):  
Yaxin Kuang ◽  
Xiaojun Gu ◽  
Zhanyuan Ye ◽  
Yun Gao ◽  
Xin Wei ◽  
...  
Keyword(s):  
Low Resolution ◽  
Detection Scheme ◽  
Smart Buildings ◽  
Ir Sensor ◽  
Occupancy Detection

scholarly journals Personal Atmosphere: Estimation of Air Conditioner Parameters for Personalizing Thermal Comfort

2020 ◽  
Vol 10 (22) ◽  
pp. 8067
Author(s):  
Tomohiro Mashita ◽  
Tetsuya Kanayama ◽  
Photchara Ratsamee
Keyword(s):  
Machine Learning ◽  
Thermal Comfort ◽  
Air Temperature ◽  
Fine Tuning ◽  
Air Conditioner ◽  
Data Set ◽  
Air Conditioning System ◽  
Air Conditioners ◽  
Uniform Distributions ◽  
Machine Learning Model

Air conditioners enable a comfortable environment for people in a variety of scenarios. However, in the case of a room with multiple people, the specific comfort for a particular person is highly dependent on their clothes, metabolism, preference, and so on, and the ideal conditions for each person in a room can conflict with each other. An ideal way to resolve these kinds of conflicts is an intelligent air conditioning system that can independently control air temperature and flow at different areas in a room and then produce thermal comfort for multiple users, which we define as the personal preference of air flow and temperature. In this paper, we propose Personal Atmosphere, a machine learning based method to obtain parameters of air conditioners which generate non-uniform distributions of air temperature and flow in a room. In this method, two dimensional air-temperature and -flow distributions in a room are used as input to a machine learning model. These inputs can be considered a summary of each user’s preference. Then the model outputs a parameter set for air conditioners in a given room. We utilized ResNet-50 as the model and generated a data set of air temperature and flow distributions using computational fluid dynamics (CFD) software. We then conducted evaluations with two rooms that have two and four air conditioners under the ceiling. We then confirmed that the estimated parameters of the air conditioners can generate air temperature and flow distributions close to those required in simulation. We also evaluated the performance of a ResNet-50 with fine tuning. This result shows that its learning time is significantly decreased, but performance is also decreased.

BLEMAT: Data Analytics and Machine Learning for Smart Building Occupancy Detection and Prediction

2019 ◽  
Vol 28 (06) ◽  
pp. 1960005 ◽  
Author(s):  
Saša Pešić ◽  
Milenko Tošić ◽  
Ognjen Iković ◽  
Miloš Radovanović ◽  
Mirjana Ivanović ◽  
...  
Keyword(s):  
Data Analysis ◽  
Experimental Validation ◽  
Building Blocks ◽  
Management Systems ◽  
Smart Building ◽  
Occupancy Detection ◽  
Occupancy Patterns ◽  
Building Management ◽  
Building Occupancy ◽  
Building Management Systems

Running costs of buildings represent a significant outlay for all businesses, thus finding a way to run facilities as efficiently as possible is vital. IoT-enabled Building Management Systems provide means for process and resource usage automation leading to overall efficiency improvements. Inferring spatial and temporal occupancy in all its forms (binary, numerical or continuous) is one of the key contextual inputs required for smart building management systems. In this work, we showcase design, implementation and experimental validation of a smart building occupancy detection and forecasting solution. The presented solution comprises three main building blocks: (1) A fog computing indoor positioning system (BLEMAT — Bluetooth Low Energy Microlocation Asset Tracking) which, combined with wireless access network monitoring processes, produces indoor location information in a semi-unsupervised manner; (2) Data analysis and pattern searching pipelines responsible for fusing data coming from different smart building and networking systems and deriving information on temporal and spatial occupancy patterns; (3) Long short-term memory (LSTM) neural networks trained to predict occupancy patterns in different areas of a smart building. Data analysis and neural network training are conducted on real-world smart building dataset which authors provide in public online repository. Experimental validation confirms that the proposed solution can provide actionable occupancy detection and prediction information, required by smart building management systems.

scholarly journals Study on energy loss and thermal environment through door open while air conditioner running

2019 ◽  
Vol 111 ◽  
pp. 06035
Author(s):  
Sihwan Lee
Keyword(s):  
Energy Consumption ◽  
Indoor Air ◽  
Room Temperature ◽  
Thermal Environment ◽  
Infiltration Rate ◽  
Operating Efficiency ◽  
Air Conditioner ◽  
Air Conditioners ◽  
Cooling Period ◽  
Closed State

While air conditioner is running, opening doors and windows is a great way to reduce operating efficiency and undermine the air conditioning system’s ability to bring the indoor to a comfortable temperature. The purpose of this study is to evaluate the heat loss and thermal environment through the door open while air conditioner running. To achieve this goal, using full-scale measurement with the commercial store during the cooling period, the infiltration rate, thermal environment and energy consumption of air conditioners with door opened and door closed state were measured. The measured results show that the infiltration rate at the door opened state was increased by about 21.3 times compared to the door closed state. When the set temperature of the air conditioner was 24 °C, the room temperature in the opening gate cooling was measured to be about 5 °C higher than the closing gate cooling. However, the energy consumption was measured approximately 12 kWh/day and there was no difference with door state. This means that the energy consumption is not increased if the indoor air temperature would not reach the set point temperature of air conditioner.

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