Data Collection Management - Building Management System - BMS

Data Collection Management

The Data Collection Module is one of the cornerstones of the Building Management System (BMS) and is critical for the healthy operation of other modules of the system. This module collects and organizes data from sensors, devices and automation systems within the building on a central platform.

It enables the effective collection of data from many sources such as HVAC, lighting, energy consumption, security systems and fire detection devices. Instant data flow allows for uninterrupted monitoring of in-building processes, while enabling early detection of potential problems and prevention of system failures.

Working with accurate data, the Data Collection Module increases operational efficiency by performing critical functions such as saving energy, optimizing maintenance processes and increasing building comfort.

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Data Collection Module

The Data Collection Module is a critical system that supports continuous monitoring of building operations, environmental management, and energy efficiency. Accurate data collection and analysis processes make building management smarter and more efficient, increasing sustainability.

Sensor Integration

Equipment Connection

Data Transmission Management

Data Collection

Data Storage

Sensor Integration

Temperature, humidity, pressure, air quality and motion sensors placed inside the building constitute the basic data source of the system. Data from the sensors are instantly transferred to the central system, so that indoor environmental conditions can be monitored without interruption. Correctly analyzed sensor data plays a critical role in energy saving and failure prevention processes.

Features

Device Identification and Integration
Protocol Management
Data Frequency and Interval Settings
Data Calibration

Device Identification and Integration
The type, model and location of all sensors used in the building are defined in the system and integrated into the central platform. In this way, the area to which each sensor belongs is determined and the correct analysis of the data is ensured.

Protocol Management:
Sensors can seamlessly transfer data using different communication protocols such as BACnet, Modbus or LoRaWAN. In this way, the system can be expanded and has a flexible structure with multi-protocol support.

Data Frequency and Interval Settings
The performance of the system is optimized by determining the data sending frequency of the sensors according to the need. While more frequent data reception is provided in critical areas, data traffic is reduced in low priority areas and the load on the network is balanced.

Data Calibration
The accuracy of the data coming from the sensors is checked and calibration processes are carried out when necessary. In this way, measurement errors are prevented and the reliability of the system is increased.

Device and Equipment Connection

It enables data collection from devices such as HVAC, lighting systems, security cameras, access control systems and energy meters. It enables different equipment to work integrated on a common platform, so that building managers can monitor all systems from a single screen.

Features

Determining Device Inventory
Network Integration
Data Flow Control

Determining the Device Inventory
The brand, model and technical specifications of all devices in the building are defined in detail. Thanks to this inventory, the status of the devices is monitored, maintenance processes are managed and control over the system is increased.

Network Integration
Devices are connected to the central platform via wired (Ethernet) or wireless (Wi-Fi, LoRaWAN) communication methods. Thus, all equipment can be monitored and managed through a single system.

Data Flow Control
Optimizes system performance by determining how often data from devices will be transferred. Network load is reduced by preventing unnecessary data flow and a healthier operation is carried out by prioritizing critical information.

Data Transmission Protocols

Common data communication protocols such as BACnet, Modbus, KNX, OPC UA allow data from devices within the building to be collected in a standard format. In this way, devices from different manufacturers can be easily integrated into the system and the BMS is provided with a flexible and expandable structure.

Features

Protocol Selection
Data Encryption
Data Synchronization

Protocol Selection
The most appropriate communication protocol is determined according to the data transmission speed, coverage area and integration needs of sensors and devices. In this way, system performance and data reliability are increased, and devices with different protocols are ensured to work in harmony.

Data Encryption
Especially in open networks such as LoRaWAN, advanced encryption methods are applied to secure data packets. In this way, unauthorized access is prevented and data integrity is maintained, increasing the reliability of the system.

Data Synchronization
Synchronization rules are defined to prevent inconsistencies that may occur in the data flow between devices operating with different protocols. In this way, data is processed correctly and consistently in all systems, making integration processes seamless.

Real Time Data Collection

It enables data from sensors and devices to be transferred to the system instantly. Thus, critical situations such as temperature changes, energy consumption fluctuations or security breaches are detected without delay. Real-time data flow enables rapid intervention and increased operational efficiency.

Features

Instant Data Stream Configuration
Data Density Management
Preventing Data Loss

Instant Data Stream Configuration
Prioritizing instant data transfer of critical devices (such as HVAC, fire alarm) prevents delays in operational processes. Thus, emergency situations are quickly detected and immediate intervention is provided.

Data Intensity Management
Intelligent filtering and sampling methods are applied to prevent overloading of the data stream. In this way, unnecessary data load is minimized, system performance is maintained and only important data is processed.

Preventing Data Loss
In order to prevent data loss, especially in wireless communication networks, retransmission protocols are implemented. In this way, information gaps that may occur due to network interruptions or signal weakening are prevented and system reliability is increased.

Data Storage and Archiving

It allows the collected data to be stored securely in a central database. This feature plays a critical role in processes such as analyzing historical data, examining trends, and planning maintenance. With archived data, past events can be analyzed and future problems can be predicted.

Features

Central Database Management
Data Archiving Rules
Data Backup and Recovery

Centralized Database Management
All data is stored in a structured central database, providing fast access and secure management. This structure allows for the smooth execution of large-scale data transactions.

Data Archiving Rules
The length of time information such as energy consumption data, maintenance history and security reports will be stored is determined to ensure the orderly operation of the system. To prevent unnecessary data accumulation, old records are archived or deleted at the end of the specified period.

Data Backup and Recovery
Daily or weekly backups are performed against possible data loss. This process, which ensures secure protection of data, enables rapid recovery in adverse situations such as system crashes or cyber attacks.