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KR-102961932-B1 - IoT and AI-based Security-enhanced Building Energy Management System

KR102961932B1KR 102961932 B1KR102961932 B1KR 102961932B1KR-102961932-B1

Abstract

The present invention relates to a building automatic control system that performs energy saving and remote management by collectively controlling building facilities (10) including mechanical facilities, power facilities, and lighting facilities installed in a building, comprising: a state detection unit (110) that detects operating state data from a plurality of operating characteristic factors installed in each of the building facilities (10) to diagnose normal operation or abnormal operation according to the characteristics of the facilities; an energy detection unit (120) that detects energy amount data of the facilities; and an environment detection unit (130) that detects environmental factor data including temperature and humidity, greenhouse gases, and fine dust inside and outside the building; A field digital control means (DDC: Direct Digital Controller, 200) that is installed in each of the pre-set partitioned spaces for each floor or room of the above building and operates based on IoT (Internet of Things) and AI (Artificial Intelligence), communicates with the detection means (100) installed within the corresponding partitioned space to collect and store data regarding the operating status, energy amount, and environmental factors, respectively, and performs on-site control to ensure that the building equipment (10) operates normally, and encodes in real time or decodes data received from the central control center (300) so that the response value obtained by comparing the collected and stored data with pre-learned AI data or the received data can be controlled on-site without hacking; The present invention relates to an IoT-AI-based security-enhanced building automatic control system comprising a central control means (CCMS: Central Control Monitoring System, 300) that communicates with each of the field digital control means (DDC: Direct Digital Controller, 200) installed throughout the building and operates based on AI (Artificial Intelligence), and includes a central encryption conversion unit (310) that decrypts the encrypted data to decrypt the encryption in real time or pre-encrypts the data transmitted to the field digital control means (200); an AI monitoring unit (320) that compares and analyzes past data clustered through a clustering AI algorithm with the data decrypted in real time, recognizes patterns, and statistically classifies them to visualize and monitor the operating status, energy consumption, and environmental factors of each building facility (10) by partition space; and a remote control unit (330) that remotely controls the operation of the building facility (10) according to the data analyzed through the AI monitoring unit (320).

Inventors

  • 박홍대

Assignees

  • 주식회사 젠탑

Dates

Publication Date
20260507
Application Date
20250516

Claims (13)

  1. In a building automatic control system that performs energy saving and remote management by collectively controlling building facilities (10), including mechanical facilities, power facilities, and lighting facilities installed in a building, A sensing means (100) having a state sensing unit (110) that detects operating state data from a plurality of operating characteristic factors that diagnose normal operation or abnormal operation according to the characteristics of the equipment, installed in each of the above building equipment (10); an energy sensing unit (120) that detects energy amount data of the equipment; an environment sensing unit (130) that detects environmental factor data including temperature and humidity, greenhouse gases, and fine dust inside and outside the building; and a data state sensing unit (140) that detects, in real time, one or more operating state data and data storage amounts among temperature, noise, shock, and video of the data storage space configured in each of the field digital control means (DDC: Direct Digital Controller, 200) and the central control monitoring means (CCMS: Central Control Monitoring System, 300); A data logger (210) installed in each of the pre-set partitioned spaces for each floor or room of the building, which operates based on IoT (Internet of Things) and AI (Artificial Intelligence), communicates with the sensing means (100) installed within the partitioned space to collect, remove noise from, and convert data on the operating status, energy amount, and environmental factors, respectively, and stores them as digital data; a field control unit (220) that controls the building equipment (10) to operate normally using a corresponding action value obtained by learning the collected and digitally converted data through IoT (Internet of Things) and AI algorithms and comparing and analyzing it with a pre-stored standard AI data model, and outputs a guidance sound or a warning sound depending on normal operation or abnormal operation; and symmetric key encryption through an AI algorithm and an encoding algorithm so that the collected and stored data, the corresponding action value, or the received data can be controlled on-site without hacking. A field digital controller (DDC: Direct Digital Controller, 200) having a field encryption unit (230) that randomly encrypts in real time using one or more encryption methods and times, including stream method, block method, factorization method, discrete logarithm method, and elliptic curve equation method of Asymmetric Key Encoding, or decrypts data received encrypted through a central encryption unit (310) in real time using an AI algorithm and a decoding algorithm; The system comprises: a central encryption unit (310) that communicates with each of the field digital control means (DDC: Direct Digital Controller, 200) installed throughout the building and operates based on AI (Artificial Intelligence), and decrypts data randomly encrypted with one or more encryption methods and frequencies through the field encryption unit (230) in real time using a decryption model learned through an AI algorithm and a decoding algorithm, or pre-encrypts data transmitted to the field digital control means (200); an AI monitoring unit (320) that compares and analyzes clustered past data with the real-time decrypted data through a clustering AI algorithm, recognizes patterns, and statistically classifies them to visualize and monitor the operating status, energy consumption, and environmental factors of each building facility (10) by partition space; and a remote control unit (330) that remotely controls the operation of the building facility (10) according to the data analyzed through the AI monitoring unit (320). An IoT-AI-based security-enhanced building automation control system characterized by including a Central Control Monitoring System (CCMS: Central Control Monitoring System, 300).
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  6. In paragraph 1, The above field control unit (220) is, An IoT-AI-based security-enhanced building automatic control system characterized by controlling the operation of the building facility (10) according to the remote control signal when a normal remote control signal is received from the central control monitoring system (CCMS: Central Control Monitoring System, 300), but controlling the building facility (10) on-site independently of the central control monitoring system (300) when the remote control signal is not received or an abnormal signal is detected due to a failure or communication disconnection of the central control monitoring system (CCMS: Central Control Monitoring System, 300).
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  9. In paragraph 1, The clustering AI algorithm of the above AI monitoring unit (320) is, An IoT-AI-based security-enhanced building automation control system characterized by selecting one or more of DBSCAN (Density-Based Spatial Clustering of Applications with Noise), HDBSCAN (Hierarchical Density-Based Spatial Clustering of Applications with Noise), OPTICS (Ordering Points To Identify the Clustering Structure), and SVM (Support Vector Machine).
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  12. In paragraph 1, The above central control monitoring system (CCMS: Central Control Monitoring System, 300) is, An IoT-AI-based security-enhanced building automatic control system characterized by further including a security enhancement unit (340) that forcibly disconnects a wired or wireless communication line and outputs a warning sound to the AI monitoring unit (320) when an unauthorized IP (Internet Protocol) accesses the system or attempts to decrypt the password more than the number of times preset in the central password conversion unit (310).
  13. In paragraph 1, The above IoT-AI-based security-enhanced building automation control system is, An IoT-AI-based security-enhanced building automatic control system characterized by further including an integrated control monitoring system (ICMS: Integrated Control Monitoring System, 400) that communicates with a central control monitoring system (CCMS: Central Control Monitoring System, 300) installed in each of the buildings to enable integrated monitoring of multiple buildings.

Description

IoT-AI-based Security-enhanced Building Energy Management System The present invention relates to a building automatic control system, and more specifically, to an IoT-AI-based security-enhanced building automatic control system that collectively controls various building facilities installed within a building based on IoT (Internet of Things) and AI (Artificial Intelligence) to achieve energy saving and remote management, and enhances security by encrypting and decoding transmitted and received data through AI and an encoding algorithm. Generally, as modern society becomes more urbanized, the concentration of the population increases, and as population density rises, the need to construct multi-unit buildings, including buildings, arises. These buildings have become larger and more functional, featuring a complex combination of various facilities such as mechanical, electrical, and lighting systems. Building Automation Systems (BAS) are being established to more conveniently monitor and control the energy-consuming equipment associated with these facilities; recently, there is a trend toward implementing Building Energy Management Systems (BEMS) alongside BAS to ensure the energy efficiency of each facility. A Building Energy Management System (BEMS) is an integrated system comprising measurement, control, management, and operation that monitors energy usage to provide optimized building energy management solutions for maintaining a comfortable indoor environment and managing energy efficiently. It controls the system to operate cooling equipment when the internal temperature rises and to operate ventilation equipment when the internal air is stale. In other words, the building control system automatically controls equipment based on specific internal and external conditions, thereby enabling the maintenance and management of a comfortable environment both inside and outside the building. For example, as illustrated in FIG. 1, Korean Published Patent Application No. 10-2019-0046293 (May 7, 2019) proposes an artificial intelligence building energy management system comprising: a sensor unit installed inside or/and outside a building; a power monitoring unit that monitors power consumed inside the building; a control unit that controls the operation of power consuming devices installed inside the building; and a management server that communicates with the sensor unit, the power monitoring unit, and the control unit through a wireless gateway and performs overall control for building energy management based on the habitual patterns of occupants inside the building. However, although the aforementioned proposed technology has led to an AI-based building energy management system, it is configured to control the operation of power-consuming devices based solely on the habitual patterns of occupants. Consequently, due to the characteristics of building energy consumption where power consumption varies depending on environmental factors such as season, temperature, and humidity, it lacks effectiveness for uniform energy management. Furthermore, for efficient device management and building energy management, there is a need to detect the normal or abnormal operating status of power-consuming devices and monitor them in real time. In addition, data transmitted and received within building energy management systems is exposed to threats of cyber terror, such as malfunctions of energy and equipment within the building, computer paralysis, and data theft, due to access by external IP (Internet Protocol). In particular, awareness regarding the need to strengthen security has increased significantly, especially after a large-scale data leakage incident caused by hacking at a major domestic telecommunications company in April 2025 resulted in severe damage to both the company and its customers. Meanwhile, as the mandatory certification of Zero Energy Buildings (ZEB) is expanding for recently constructed buildings—which are green buildings designed to minimize energy consumption by utilizing renewable energy and minimizing the energy load required for the building in accordance with energy conservation and greenhouse gas reduction obligations—there is a need to devise a building automation control system as a building energy management system that manages and controls building facilities' energy more efficiently and offers enhanced security. FIG. 1 is a drawing illustrating an artificial intelligence building energy management system according to the prior art. FIG. 2 is a block diagram showing the overall technical configuration of an embodiment of an IoT-AI-based security-enhanced building automatic control system according to the present invention. FIG. 3 is a drawing showing a central control means communicating with a field digital control means and a sensing means installed in one partitioned space within a building, respectively, based on the embodiment of FIG. 2. FIG. 4 is a block diagram showing the detailed conf