Smart firefighting" construction as a part of the "smart city" has been a concern of the public security and fire agencies at all levels. In this study, the status, problems, and reflections of "smart firefighting" construction in China are discussed. A recent survey indicates that China has launched its smart firefighting construction and initially created a new perspective on its regional smart firefighting work based on three main aspects: intelligent disaster perception by Internet of Things (IoT) construction, intelligent disaster prevention by big data construction, and intelligent disaster disposal by emergency rescue platform construction. However, the current smart firefighting construction in China still has some prominent problems such as the data interconnectivity and normalized management of various platforms, the extensibility of smart firefighting platforms, and the intelligent level of smart firefighting researches, which need to be solved urgently. Therefore, we argue that smart firefighting construction in China should establish data interconnectivity, industrial normalized management, 2D/3D geographic information interaction and extension, high-integration fire protection theory, and many other aspects in the near future and truly realize firefighting visualization and efficient data applications for 4D time space. This study could provide valuable reference for smart firefighting and smart city construction.
Investigating the behavior of fire smoke in utility tunnel as well as smoke prevention and control measures are of vital significance for exhausting smoke from utility tunnel, realizing efficient firefighting and rescue, and guaranteeing the normal operation of cities. Taking utility tunnel as the research background, this paper builds a simulation calculation model for fire smoke prevention and control in the utility tunnel using PyroSim numerical simulation software and explores the rules of smoke spread under conditions such as building ceiling screen, changing fire compartmentation tightness, and adding smoke exhaust facilities. According to study results, before the tunnel was filled with smoke, ceiling screens lowered smoke spread rate, and smoke spread rate was inversely proportional to the ceiling screen height. When the fire door was opened, fire smoke spread to the adjacent fire compartment, and smoke spread rate was directly proportional to the fire door opening angle. Before the tunnel was filled up, mechanical smoke exhaust facilities significantly lowered the smoke spread rate by as much as 50%. When the entire tunnel was full of smoke, mechanical smoke exhaust facilities significantly reduced the smoke concentration in the utility tunnel; smoke layer temperature dropped by as much as 32°C, while visibility improved by as much as 66%. By studying smoke spread in utility tunnel, this paper aims to determine the optimal measures of preventing and controlling smoke spread in utility tunnel. This paper could also offer some reference for practical engineering applications in smoke prevention and control in utility tunnel.
In order to study the application of Internet of things energy system in complex fault risk dynamic assessment of transmission line. Firstly, the concept of power grid dynamic risk assessment is introduced, and the process of power grid dynamic risk assessment system based on Internet of things is designed. Then, it puts forward how to use the ubiquitous Internet of things multisource data to solve the key problems such as dynamic perception of fault probability, dynamic selection of fault set, dynamic generation of post fault state, and dynamic risk assessment of operation process. Finally, taking the maximum operation mode of a provincial power grid in summer 2013 as an example, this paper selects key 500 kV transmission lines for risk assessment, and the actual power grid example shows that. The power grid comprehensive risk assessment system considering the fault characteristics of transmission lines can effectively predict the fault probability of transmission lines; distinguish the two risks of high loss, low probability, and low loss and high probability; and provide guidance for operators. It is practical and effective.
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