Yet it is precisely this unseen layer that becomes one of the most overlooked and difficult-to-control weak points in urban safety governance. According to China's Ministry of Emergency Management, between 2013 and 2022, the industrial and trade sector recorded 95 major confined-space accidents, resulting in 357 deaths. Poisoning and asphyxiation accounted for 96.8% of these cases, with hydrogen sulfide and carbon monoxide poisoning making up over 80%. Behind each statistic is a lost life, a broken family, and a recurring safety question that remains unresolved. Septic tanks, underground valve chambers, sewage pipelines, and utility corridors are typically narrow, poorly ventilated, and prone to the accumulation of toxic gases that cannot be sensed by human perception. One impulsive entry can trigger a chain of poisoning, suffocation, or explosion. One untrained rescue attempt can multiply casualties. For example, methane buildup in confined spaces can reach pressures up to four times that of a car tire. The explosive force of just one cubic meter of biogas is equivalent to 0.66 kilograms of TNT—enough to destroy chambers and rupture road surfaces. Even more alarming, sewage wells and septic tanks often contain extremely poor ventilation, allowing hydrogen sulfide to reach lethal concentrations that can cause "flash death," where workers collapse within seconds of entry.

A septic tank explosion in Sichuan overturned nearby vehicles

The risk of confined spaces is fundamentally the risk of the invisible. And invisible threats are the hardest to defend against. This exposes a structural limitation of traditional safety paradigms: for a long time, safety has relied on a post-incident logic—rescue after accidents occur, correction after risks emerge. While this model may function in relatively controlled environments, it becomes dangerously insufficient in confined spaces that are unseen, inaccessible, and difficult to measure. No matter how comprehensive the regulations or frequent the training, as long as humans must still enter shafts, rely on experience, and respond only after danger appears, there remains an irreducible residual probability of accidents. This is not a failure of execution, but a structural limitation of the traditional safety framework when confronting complex hidden environments—it is always one step behind risk, often at the cost of life.

In 2024, an accident occurred at a factory in Hunan Province involving confined space operations, resulting in the deaths of two people

In the era of digital intelligence, safety is shifting from "post-incident response" toward a new paradigm of resilience where prevention and response coexist. This is not a simple technological upgrade, but a fundamental transformation in safety logic. Prevention refers to perception, early warning, and intervention before risks materialize. Response refers to the ability to react rapidly and precisely once risks break through defenses, minimizing damage. Resilience means these two functions are not separate stages, but an integrated, mutually reinforcing system—where each response feeds back into improving predictive models, and each prevention gap drives upgrades in response capability. This cyclical relationship between prevention and response forms the foundational logic of safety governance in the digital era. This is precisely what Qingqiao understands as the "path of digital safety adaptation": neither rejecting technology nor blindly trusting human effort, but finding the optimal coexistence boundary between sensing and response, prediction and intervention, system and field reality.

Why does Qingqiao choose to do this? The answer begins with its underlying nature. Qingqiao is a security company, but its understanding of "security" has never been limited to guard posts, patrols, access control systems, or surveillance cameras. Traditional security systems have laid the foundational layer of social safety over past decades, yet their boundaries are equally clear: human resources are finite, visibility is limited, and response is inherently delayed. As cities become more complex and risks more concealed, a purely manpower-based security model is reaching its ceiling. Qingqiao's choice is to use confined spaces as its entry point and to establish a new paradigm of "resilient coexistence between defense and response," thereby forging a breakthrough path in security. Confined spaces are not chosen because they represent a "technological blue ocean," but because they are the ultimate testbed for validating this new paradigm. If even spaces that cannot be seen or physically entered can be integrated into a system that is perceivable, controllable, and actionable, then other scenarios can adopt a reusable methodology for safety upgrades. Confined spaces are the most difficult exam in digital-intelligent safety, and Qingqiao chooses to start from the hardest point.

Based on this judgment, Qingqiao systematically analyzed where exactly the difficulty of confined-space safety lies. The first pain point is "invisibility." These spaces are buried underground, where gas conditions, liquid levels, and structural states cannot be observed through sight or routine inspection. Risks exist like hidden currents but remain undetectable, forming a blind zone in defense. The second pain point is "inaccuracy." Traditional portable detectors rely on manual entry into shafts, with limited sampling points, discrete timing, and significant human error. Each measurement only reflects one moment and one location, failing to capture dynamic changes, resulting in fragmented defense. The third pain point is "delayed response." Even when anomalies are detected, the time required from alarm to on-site arrival and intervention often exceeds the optimal response window. Worse, blind rescue efforts can turn minor risks into major disasters, creating latency in response. The fourth pain point is "disconnection." Many wells and pipeline corridors exist as isolated information silos, with data not uploaded, not networked, and not aggregated. City managers cannot achieve holistic situational awareness, let alone data-driven decision-making, resulting in a lack of resilience. These four pain points overlap and reinforce each other, forming an "impossible triangle" in confined-space safety governance: humans cannot enter, equipment cannot sustain effectiveness, and data cannot be connected. If any one side fails, safety cannot be truly closed-looped.

To break this "impossible triangle," action must be taken simultaneously across four dimensions. First, use sensing to eliminate blind spots by deploying sensors in every shaft and every segment of pipeline corridor, transforming previously invisible risks into quantifiable data streams. Second, use continuous monitoring to bridge fragmentation by abandoning discrete manual inspections and establishing a 24/7 uninterrupted data acquisition channel, ensuring risk evolution is no longer discontinuous or unknown. Third, use intelligent early warning to eliminate delays; when data anomalies exceed thresholds, the system triggers alerts within milliseconds, compressing the response window from hours to seconds and fundamentally shifting the paradigm from "humans waiting for risk" to proactive intervention. Finally, the real qualitative leap comes from integrating data analytics with large-model systems, enabling the formation of digital value that is storable, reusable, and continuously evolvable. Large models are not a gimmick, but the "intelligent hub" of confined-space safety governance. They can learn risk evolution patterns from massive historical data, identify complex risk modes that are difficult for humans to detect, predict potential abnormal trends, and provide explainable decision support for early warning and response. More importantly, large models transform data from disposable records into digital assets that continuously optimize defense strategies and iteratively improve response plans. When data streams from sensing, monitoring, and early warning enter the model for analysis and reasoning, every risk event feeds back into the system's cognitive capability, and every successful intervention strengthens its decision accuracy. This is how resilience is forged: not as static robustness, but as dynamic learning and evolutionary capability. Data is the fuel, the large model is the engine, and resilience is the system's ability to continuously operate, adapt, and self-improve under uncertainty.

On April 8, 2026, Qingqiao officially launched its confined-space intelligent monitoring and early warning terminal, G5687-ST2501. This multi-gas detection device is specifically designed for confined and enclosed environments such as underground pipeline networks, septic tanks, and sewage wells, where ventilation is poor and toxic or flammable gases can easily accumulate. Its release marks the official implementation of Qingqiao's 1.0 product. In terms of safety and environmental adaptability, the G5687-ST2501 has passed rigorous evaluation by the National Safety Inspection and Testing Center. It obtained the explosion-proof certification Ex ia IIC T4 Ga, representing the highest level of intrinsic safety explosion-proof standards. This allows it to operate safely in highly explosive gas environments and other extreme high-risk conditions. The device has also passed salt spray corrosion resistance tests and safety protection assessments, enabling stable operation in a wide temperature range from -10°C to +60°C. It is resistant to high humidity, high salinity, and corrosive acidic or alkaline conditions commonly found in coastal and industrial environments. In terms of detection accuracy, the device achieves performance at an upper-mid industry level across key indicators. It also integrates LiDAR technology for liquid level detection, further enhancing multi-dimensional situational awareness in confined spaces. From the perspective of resilience as the coexistence of defense and response, the G5687-ST2501 acts as the "forward sensing outpost" of the perception layer, providing precise, continuous, and multi-dimensional data that serves as the foundational fuel for the entire resilience system.

However, Qingqiao is fully aware that 1.0 is only the starting point. The real bottleneck in confined-space monitoring has never been "whether detection is possible," but rather "whether it can be deployed long-term, stably, and at low cost." At present, many monitoring devices are too large, too complex to install, and too dependent on external power supply, resulting in actual deployment rates far below policy expectations. Therefore, the upcoming 2.0 product will introduce major breakthroughs in size, industrial design, energy storage, and power supply methods. A smaller form factor will better adapt to narrow shaft spaces. A more rational structural design will reduce installation and maintenance complexity. A more efficient and reliable energy storage system will reduce dependence on external power sources. The essence of 2.0 is a shift from "technically feasible" to "engineerable at scale." Only when monitoring terminals become sufficiently small, energy-efficient, and durable can the sensing network expand from pilot projects to millions of nodes. Only then can resilience truly extend down into every single shaft. The second-generation product is already in development and is expected to enter production in six months.

The Qingqiao Confined Space Smart Monitoring and Early Warning Terminal G5687-ST2501 has been put into use

Facing the present, Qingqiao's core focus is how to achieve highly reliable, low-power, maintenance-free long-term monitoring in complex, harsh, and confined underground environments; how to deeply integrate massive monitoring data with large models to form evolvable digital value; and how to lower deployment and operational barriers so that safety capabilities can extend to the most overlooked "last kilometer" shaft wells. At present, the G5687-ST2501 has been successfully piloted in more than ten enterprises and public institutions. In real-world scenarios, the product has validated its detection accuracy under multi-gas interaction conditions, its operational stability in harsh environments, and the engineering feasibility of remote maintenance. Looking ahead, Qingqiao faces more far-reaching questions: when sensing, continuous monitoring, intelligent early warning, and large-model-based analysis form a complete data value chain, can confined-space incidents truly be prevented before they occur? When every shaft and every section of pipeline corridor is equipped with full capabilities of perception, analysis, decision-making, and response, can urban lifeline systems achieve a leap from "resilience" to "immunity"? As digital-intelligent safety extends from confined spaces to broader urban security scenarios, can the "ceiling" of traditional security models truly be broken? And does this represent a strategic anchor point and breakthrough path for the transition from traditional security to digital-intelligent security?

We often say that a city is a living organism. Its resilience does not depend on how tall its buildings are or how wide its roads become, but on the invisible places: whether they are safe enough, reliable enough, and truly observable. Real safety is not luck, nor chance, nor post-event remediation. It emerges from a system where defense and response coexist in resilience. It is the pursuit of certainty in unseen spaces. This is not only a technological choice, but also a paradigm shift in safety thinking, from post-event response to resilient co-evolution of defense and response. Qingqiao, probe to the end.