Internet of things-based study on online monitoring system of building equipment energy saving optimization control using building information modeling

Science Progress, Год журнала: 2024, Номер 107(2)

Опубликована: Апрель 1, 2024

Smart building equipment monitoring is a well-established field focused on enhancing contemporary comfort. The proliferation of Internet connectivity, facilitated by the internet things (IoT), has transformed buildings from static structures into interactive environments. IoT witnessed substantial growth across various aspects daily life, environmental conditions to managing systems and storing data in cloud. One critical application intelligent control equipment, such as air conditioners, optimize energy efficiency-a matter increasing concern for owners, design experts, system integrators. Achieving comprehensive savings demands meticulous approach energy-efficient control. This paper's primary objective explore analyze IoT-based energy-saving optimization techniques integrating information modeling (BIM) technology. It particularly delves conservation algorithm air-conditioning systems. research presents challenge rooted optimization, established upon specific functions, followed detailed explanation algorithm. To validate their approach, paper outlines experimental design. Over three sessions August, they conducted experiments two distinct areas. Area 1 implemented methodology discussed paper, utilizing virtual parameter enhancement mechanisms, while 2 adhered conventional methods. results were enlightening. demonstrated superior efficiency, consuming 735 kWh compared 2's 819 kWh, signifying an impressive 11.43% reduction consumption thanks optimized strategy. underscores practicality significance implementing strategies, with focus smart thermostats, HVAC controllers, daylight sensors, management achieve gains.

Язык: Английский

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Data-driven Technology Applications in Planning, Demand-side Management, and Cybersecurity for Smart Household Community

IEEE Transactions on Artificial Intelligence, Год журнала: 2024, Номер 5(10), С. 4868 - 4883

Опубликована: Июнь 20, 2024

Язык: Английский

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Review of Artificial Neural Network Approaches for Predicting Building Energy Consumption

Опубликована: Март 6, 2023

Recently, the forecasting of energy consumption has prompted a massive escalation in research studies that are being conducted all over world an effort to attain higher levels sustainability. Forecasting is essential decision-making for effective conservation and development within organization. The adoption data-driven models seen tremendous growth past few decades as result improvements performance, robustness, simplicity deployment brought about by these improvements. There various kinds models, but Artificial Neural Networks (ANN) currently among most widely used methods have been applied real-world situations. This study provides comprehensive overview on ANN comparison with other evaluation metrics were employed evaluate performances each technique. review helps outline potential future area building prediction prominence existing gaps.

Язык: Английский

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Optimizing Smart Home Appliance Energy Monitoring using Factorial Hidden Markov Models for Internet of Behavior

Journal of Building Engineering, Год журнала: 2024, Номер unknown, С. 110732 - 110732

Опубликована: Сен. 1, 2024

Язык: Английский

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Two-stage optimal configuration and control based on virtual hybrid energy storage

Journal of Energy Storage, Год журнала: 2024, Номер 103, С. 114167 - 114167

Опубликована: Окт. 25, 2024

Язык: Английский

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