Biosafety LaboratoryAs the core site for the research and detection of pathogenic microorganisms, its environmental stability and operational standardization are directly related to experimental safety and data reliability. As the "nerve center" of laboratory safety control, the intelligent monitoring system needs to focus on the core of risk prevention and control, and build an integrated system of "full dimensional perception, intelligent analysis, and rapid response" to provide comprehensive guarantees for the safe operation of the laboratory. The core construction strategy can be developed from the following four aspects.

Accurately define monitoring dimensions and achieve full scene coverage. Before construction, it is necessary to clarify the core risk points of the laboratory and determine the monitoring scope. In terms of environmental parameters, the focus is on monitoring temperature and humidity, pressure difference (especially in biosafety cabinets and negative pressure laboratories), cleanliness, airflow direction, as well as key indicators such as CO ₂ concentration (in cell culture areas) and formaldehyde/ozone concentration (in disinfection areas); In terms of security protection, real-time monitoring of the operation status of the biosafety cabinet, pressure and temperature of the high-pressure sterilizer, and air volume of the ventilation system, equipped with access control and personnel positioning systems, recording the identity, time, and activity area of personnel entering; In terms of emergency prevention and control, modules such as water leakage detection (laboratory bench, cold storage area), fire alarm, and pathogen leakage monitoring (high-level laboratory) will be added to ensure no blind spots in monitoring.

Build a layered technical architecture to enhance system stability. Adopting a four layer architecture pattern of "perception layer transport layer platform layer application layer". The sensing layer uses high-precision and high stability sensing devices, such as Swiss Rozhnick temperature and humidity sensors, HEPA filter integrity monitors, etc., to ensure accurate data collection; The transmission layer adopts a "wired+wireless" fusion mode, with core devices (such as pressure difference, temperature and humidity) transmitted through industrial Ethernet, and mobile devices (such as personnel positioning tags) using 5G or WiFi 6 technology, equipped with redundant transmission channels to avoid data loss; The platform layer builds an intelligent hub for cloud edge collaboration, while the edge end implements real-time data preprocessing and local alarms. The cloud is responsible for data storage, big data analysis, and remote control; Develop a visual monitoring interface at the application layer, supporting access on both PC and mobile devices, enabling real-time parameter viewing, historical data tracing, and report generation.

Enhance intelligent analysis capabilities and improve risk warning efficiency. Building intelligent analysis models based on artificial intelligence and big data technology. By using machine learning algorithms to train historical data, accurate identification of abnormal parameters can be achieved. For example, when the laboratory pressure difference fluctuates beyond the ± 5Pa threshold, the system automatically determines it as an abnormality and issues a warning; Set up a multi-level warning mechanism, divide warning thresholds according to risk levels, trigger SMS reminders for low-level anomalies (such as slight fluctuations in temperature and humidity), and immediately activate sound and light alarms and emergency equipment linkage (such as activating exhaust systems and closing access control in experimental areas) for high-level risks (such as pathogen leaks and fires). At the same time, establish a device lifecycle management model, analyze device operating parameters, predict maintenance needs such as filter replacement and sensor calibration, and achieve proactive operation and maintenance.

Improve data security and emergency mechanisms to ensure the reliable operation of the system. In terms of data management, AES encryption technology is used to transmit and store monitoring data, and the data backup system (local+cloud dual backup) is strictly implemented, in compliance with the data traceability requirements of the "Technical Specification for Building Biosafety Laboratories"; In terms of emergency response, a pre-set emergency plan template is used. When an emergency situation occurs, the system automatically pushes the emergency response process to the management personnel terminal, links relevant equipment to initiate emergency measures, such as automatically shutting down the ventilation system and turning on the fire extinguishing device when a fire alarm is triggered. At the same time, the entire emergency response process is recorded to provide a basis for subsequent review. In addition, regular system debugging and drills are conducted to ensure smooth collaboration between equipment and software.

The intelligent monitoring system constructed through the above strategy can achieveBiosafety LaboratoryThe refinement and intelligence of control measures have shifted from passive response to active prevention and control, effectively reducing experimental risks and laying a solid technical foundation for the safe operation of laboratories and the smooth progress of scientific research work.