An Approach to the Environment of Urban Building Fire Safety Based on Internet of Things

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An Approach to the Environment of Urban Building Fire Safety Based on Internet of Things Yin Ke*1, Jiang Juncheng College of Urban Construction and Safety Engineering, Nanjing University of Technology, Nanjing Jiangsu 210009, China Mail Box 13, No. 200, North Zhongshan Road, Nanjing University of Technology, Nanjing 210009, China jcjiang@njut.edu.cn Abstract The Internet of things has become a key technology in urban safety engineering and, even an important part in our modern family life nowadays. Therefore, it has become one of the important methods used in the development of information network technology of fire protection system. In this paper, we applied the IoT technology in the building fire to create a dynamic model of analysis based on the relevant location algorithm, by which a better dynamic monitoring system of fire control was constructed in the two different environments, which can provide an important reference for the information system construction of fire protection and the scientific management.

Key words IoT; Urban Building; Fire Safety; Dynamic Monitoring

Introduction In recent years, the IoT has rapidly drawn wide attention of both home and abroad. On December 8, 2011, the Ministry of Industry and Information Technology of the People’s Republic of China released the 12th Five-Year Plan on IoT, of which seven main tasks involve "the construction of standard systems of IoT," and "the demonstration of active application of IoT". Against the background of the national strategies of "sense China", great attention from the academe, industry, and government to IoT has successfully been transformed from a concept to an industry. Nowadays, IoT has got much priority applied in a lot of fields such as the intelligent transportation, environmental monitoring, public safety, industrial control, medicine and health.

As a new technology, urban public security also pays much attention to IoT, since IoT can help the management of urban public security in many respects.

A series of incidents such as Shanghai JingAn Fire and Nanjing Chemical Plant Explosion warns people: the

foundation of Urban Public Safety Emergency Management is very weak in our country; especially the fire safety situation is still far from satisfactory.

How to prevent and deal with urban public safety incidents with IoT technology becomes a very urgent topic, which is worth much researching. Uwe Rueppel (Uwe, Kai 2008) constructed a BIM system based on IoT technology for evacuating people from dangerous place inside the building. Ma Xin (Ma, Huang 2010) proposed a framework of public security network, making some related researches by combining IoT with fire area. These researches have often been cited as the successful items in urban safety. But their researches mainly focus on the specific aspect, such as the building model of evacuation, the constructing monitor systems of fire, so that there are few researches on the integrated application of IoT in architecture fire systems.

As known, IoT has three outstanding characteristics: overall perception, reliable transmission, and intelligent processing, which can properly meet three basic requirements in the fire safety management of fire control, fire alarm and fire rescue, respectively.

However, there are few reports on making full use of the three functions of IoT together in urban building fire safety. Therefore, this paper intends to divide the stage of building fire into two parts, based on IoT technology, and tries to make an exploration to the feasibility of its application in urban fire protection and fire safety field, expecting the construction of an effective in time fire warning and monitoring system based on IoT. A Brief Survey of Internet of Things Internet of things is based on Internet, using RFID (Radio Frequency Identification), wireless data 1

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communication technology to construct "Internet of Things" with coverage of all things in the world. In this network, things "communicate" with each other, without intervention of human, whose essence is the use of RFID technology to realize the automatic identification and information sharing of things through the Internet.

and fire-fighting equipments) to realize the RFID tag information and have access to relevant data, to identify the work effectively without human intervention in the various complex fire environments.

IoT is also known as sensor network, referring to a vast network by means of combining various information sensing device such as RFID, infrared sensors, GPS, laser scanners and other various device with the Internet(Tu, Wang 2010). So, one of the definitions of the IoT is given as ‘a self-configured dynamic global network infrastructure with standards and interoperable communication protocols where physical and virtual ‘things’ have identities, physical attributes, and virtual personalities, and are seamlessly integrated into the information infrastructure’ (European Commission 2012).

At present, IoT application approach in the public fire protection field mainly focuses on the monitoring, i.e.

Damian Gallegos from University of New Mexico applied wireless sensor technology to the forest fire protection, and established a kind of effective fire early warning and monitoring system (Damian 2003).

Stanford University developed a building monitoring system based on wireless sensor network for the use of monitoring and periodic test of fire accident (Du, Zhu 2012). Besides, some equipments inside (such as elevator) and outside the building (such as fire extinguishers, fire alarm equipment) have also been introduced into the concept of IoT (Zhu, Wei et al.

2010).

The Building Fire Protection and the Key Technology of Internet of Things In 2005, the International Telecommunication Union (ITU 2005) released ITU Internet Reports 2005: The Internet of Things, which formally gave a complete concept of "Internet of things": the Internet of things is the extension of internet applications, "RFID, WSN (Wireless Sensor Networks), intelligent technology, nanotechnology" will be the four core technologies of Internet of things. These four kinds of core technologies also play an important role in each field in the building fire. Among them, the RFID, the foundation and networking core of the construction of IoT(Li, Yu 2011), is a new automatic identification technology of non-contact automatic identification, identifying the moving or static target by RF signal (for example: distressed personnel, personnel to be rescued

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WSN is a network system of retrieving, transmission and processing of distributed data on the Internet of things, and it is also a channel and means that helps to realize each function of the system. So, IoT can be used to carry on the real-time monitoring statically and dynamically through the sensor nodes all over the inside of the building by the sensing network. It is known that there are various kinds of RFID and WSN development of the network protocol such as ZigBee (ZigBee Alliance 2013), 6LoWPAN (IETF 2013) and UWB (Ultra Wideband), Shen Xuesong (Shen, Chen 2008) applied WSN in the resources tracking in building construction, and analyzed the different network protocols in detail.

As one of the key technologies of intelligent science and network, the IoT has become the inevitable product of the rapid development of the intelligent technology, which appropriately meets the needs of the intelligent terminal development. The intelligent technology is widely used through the embedded technology with intelligent system embedded in the object, so it can perform intelligently in the internet of things, and these intelligent detectors can be different according to the threshold of flexibly switching modes, providing more accurate in time warning information while reducing energy consumption.

So, application of nanotechnology in building fire has been mainly found in the aspects of microminiaturization design of various sensing devices, with the typical features of sensor microminiaturization in fire-fighting equipment and the feature of reduction in energy consumption. The carrier stored with all kinds of data and information is miniaturized so as to be easily installed in a variety of objects without affecting its normal operation and circulation. The use of nanotechnology implies that the IoT technology can be used in a smaller volume of fire-fighting equipment, for example, the active RFID tag, which is the successful combination of intelligent technology and nanotechnology.

Application of IoT in the Field of Fire Safety As a multidisciplinary, the IoT involves many research areas such as hardware, short distance data transmission, network, data fusion and accident decision. So, it is quite realistic to apply the IoT

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technology in the field of building fire, that is, to apply IoT to integrate all kinds of technologies and apply them into the specific work of each stage in the fire.

This thesis will mainly discuss the building fire protection process in two stages based on the application of the key technology of IoT: intelligent management and intelligent command. Here, by the intelligent management we mean the prevention and early warning in building fire, and by intelligent command, the emergency rescue and command after the fire.

using RFID readers, and according to the residual weighting algorithm between different labels, a higher location accuracy can be obtained. This model is considered to be the active dynamic positioning recognition technology with a better performance (see Fig. 1).

Intelligent Management of Building Fire Safety System IoT has been widely used in building fire system, and especially in the construction of fire equipment and personnel density monitoring. According to the analysis of the causes of fire in high-rise buildings, several common problems can easily be found: 1) how to deal with the lack of effective management to fire-fighting equipment and supervision in daily maintenance after initial acceptance in building; 2) how to obtain the parameters of key areas and danger sources accurately and timely; 3) how to find emergency rescue methods in crowded place.

According to the Model, readers continuously read the information transmitted from RFID tags, and the received signal strength is defined as the Signal Strength Vector. Since the tags are classed into tracking and reference tags, the Signal Strength Vector of a tracking tag is represented as S=(S1,S2,…,Sn) where Si denotes the signal strength of the tracking tag perceived on reader i, where i=1,…,n. And the Signal Strength Vector of a reference tag is denoted as θ=(θ1,θ2,...,θn) where θi is the signal strength of the reference tag perceived on reader i, where i=1,…,n.

Each RFID reader will receive the two types of data and for each individual tracking tag p, where p=1,…,u, we define

= Euj

n ∑ i =1 (θ ji − Sui )2 j ∈ (1, m)

(1)

Euj is the Euclidean distance in signal strength between a tracking tag and a reference tag rj. The Euj value means the location relationship between the reference tags and the tracking tag. If there are m reference tags, a tracking tag will have its E vector as E=(E1,E2,…,Em).

Therefore, the nearer reference tag to the tracking tag is supposed to have a smaller E value (Guo 2009).

The weights assigned to different neighbors:

1 wj =

∑

k

i =1

2

Ei 1

Ei

2

(2) wj is the weighting factor to the ith neighboring reference tag.

FIG. 1. LANDMARC MODEL

As known, the key point of indoor active surveillance application of IoT is the RFID indoor locating technology, including the SpotoN model and 3D-iD indoor locating technology based on RF (Radio Frequency), which is similar to the SpotoN method, using wireless local network technology to locate.

These two kinds of technologies are of high reliability, but the investment of the system is often too large.

Lionel etal used LANDMARC (LocaAtioN identification based on dynamic Active Rfid Calibration model (Lionel, Yunhao et al. 2003), introducing the reference tags to reduce the need of

After the weight being obtained, the computed tracking tag location(x,y):

( x, y ) = ∑ ik=1 wi ( xi , yi )

(3)

In the end, the error distance is used to check the LANDMARC system, according to the computed coordinates(x,y) and the real coordinates(x0,y0), the error value can be obtained so as to improve the correlated parameters.

The inside building fire safety hazards are inevitable if we depend only on the long-term artificial check-out, and what’s more, the accuracy of fire equipments requires a higher professional level, that is, the long persistence and higher reliability (Zhang, YU 2013).

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Therefore, the building of network system is quite necessary. Once the equipment fault occurs, the network system can find it in time and inform relevant departments to make some maintenance. And the equipment manufacturers can also trace to the location of the faulty device, and make some maintenance or repairing. Besides, in the daily management of fire protection system, we can use LANDMARC model to obtain accurate information whether it is normal to use fire equipments or to locate the ignition position timely, and especially when facing the dense population flow in the building, we can not only monitor the real-time flow density, but also do some simulation and verification together with LANDMARC system, by asking the relevant personnel to wear the embedded RFID tags and comparing them with the indoor fixed labels so as to dredge personnel orderly and effectively.

Therefore, the application of IoT in fire safety management inside the building can not only play an effective monitoring role in the firefighting equipment maintenance, but also, provide the early warning of dangerous area to the supposed targets in dense population.

rescue vehicle location and route location, but it is only suitable for outdoors. Here, the Internet of things can help us a lot in the fire fighting and rescue by combining the outdoor GPS system with the indoor real-time location system. The indoor location system mainly includes RTLS (real-time location systems) if the position is updated within an interval of one minute (Uckelmann, Hofmann 2008) based on ISO/IEC 24730 systems for position sensing. RTLS works mainly on WSN technology to collect data information through the indoor positioning algorithm to build a dynamic analysis model. WSN protocol including 802.11x wireless local networks (WLAN) (Wi-Fi) and 802.15x wireless personal area networks (WPAN) (Bluetooth, UWB and ZigBee). Position sensing via RF is based on calculation of the distance between sender and receiver (antenna). Normal RF RTLS have to cope with overlapping signals of the direct signal and signals reflected from walls, windows, etc. (multipath effect). The advantage of UWB is the use of very short pulses which are possible because of a wide range of frequencies.

Fire-fighting Intelligent Command and Emergency Rescue The fire of buildings occurs often out of expectation.

And the complexity of structures between layers in the high-rise building increases the difficulty of fire fighting. When fire occurs, the fire spreads fast usually in chimney effect, so it is quite necessary to improve the efficiency of fire emergency rescue. However, building fire rescue is often confronted with many difficulties: (1) the quick spread of fire and the different vertical wells such as elevator wells, tube wells, air duct, cable wells, and stairways in high-rise buildings often make personnel rescue resort to personal experience, which is often accompanied by lack of communication with the outside world, the lack of a uniform dispatch and control-all of which can never help to search for the trapped effectively, not to speak of the latest dynamic state of the fire. (2) The evacuation difficulty, by which we mean that people concentrate in high-rise buildings, and that it is difficult to know accurately the personnel distribution and flow condition within the building. (3) The difficulty in deciding the routes of rescue vehicles, since traffic in modern city streets is often jammed and the routes between buildings are quite complex so that rescue vehicles can not get near to the fire in time, which often leads to the delay in rescue.

Of course, GPS technology can provide the help for the 4

In the indoor fire rescue, such parameters as the concentration of indoor harmful gases including carbon dioxide, the air humidity, the flame trend, and the location of indoor personnel and rescue workers will be collected into a relevant radio frequency module, which will be sent to the analysis module of the host computer by the set-up WSN based on UWB technology. The indoor localization algorithm based on UWB technology mainly includes four different measurement principles: angle of arrival (AOA), received signal strength indication (RSSI), time of arrival (TOA), and time difference of arrival (TDOA).

Based on the technologies above, we designed a data location model to set up a monitoring network including the trapped people inside and outside the firing building, the fire rescue personnel and the vehicles positioning (see Fig. 2).

FIG. 2 UWB-BASED NET MODEL

Urban Planning and Design Research (UPDR) Volume 2, 2014

The network model consists of fixed nodes, mobile nodes and control nodes. The fixed nodes refer to the set sensor nodes embedded inside the building in advance; and the mobile nodes are attached to the trapped personnel and the rescuers, including RFID tags and GPS communication equipment; in addition, the control nodes are used usually to collect all the information of personnel and equipments related.

Thus, the monitoring network works effectively by cross contrast with the information of the fixed nodes and that of mobile nodes, while the fixed nodes, as reference nodes at the same time, will transfer the information of the temperature and environment in the relevant area to the control nodes in real time. Due to the adoption of UWB technology, the information from mobile nodes can be stably and efficiently transmitted to the control nodes. By excluding the interference from the distress site, the mobile nodes can directly reflect the staff's temperature, pulse and the parameters of surrounding air. And at the same time, based on the information from fixed nodes, the control nodes will analyze the data and information in models, and then construct a three-dimensional model. By means of the TOA model (Cui, Zhang et al. 2011) or RSSI (Gabriel, Kevin et al. 2013) model, we can calculate our location, and locate the position of trapped personnel and the marching route effectively.

Thus, a wireless sensor network area can be built both inside and outside the firing building, and then the commanding personnel can judge the spread of the fire inside the building through the rescue personnel in the fire spot and take direct and effective measures. More important is when we get the information about the location and physical status of trapped persons and rescue personnel, we can make reasonable planning of rescue and evacuation routes in time so as to guarantee the safety of the related personnel successfully.

Conclusions The application of IoT in fire safety is one of the important developmental trends in the informatization of fire systems. This paper has made an exploratory application of IoT technology in the building fire, analyzing the construction model and positioning algorithm based on the two kinds of different fire environment features. A dynamic monitoring system of fire control has been put forward which can be quite useful in the establishment of the information system of fire control system. With the application of this system, the loss of property as well as the risk of the personal danger can be reduced.

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The development of the IoT technology has been quite mature, but it is very scarce to combine it with the building fire controlling. A follow-up study will include three aspects: (1) how to establish a dynamic model in the key areas crowded with dense population, and then make a plan of the best path of evacuation and rescue when fire happens; (2) how to use a sensor in the invisible environment to obtain the parameters of temperature, pressure, and air concentration and then analyze the disaster so as to simulate the disaster development on line; (3) how to exclude the different interference such as indoor noise, high temperature, etc. and make full use of the wireless sensor networks to locate and monitor the rescuers and rescue quickly and accurately, in order to make the informatization system of fire control system above more effective.

ACKNOWLEDGMENTS

Yin Ke acknowledged the support of Jiangsu Graduate Scientific Innovation Projects.

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Ke Yin is Ph.D of Safety Technology and Engineering in Nanjing University of Technology in China. Currently he pursues his Doctorate in the research field of information management, urban public safety and risk management. His research interests focus on information management, urban public safety and risk management in Nanjing University of Technology until 2014.

Juncheng Jiang is a Professor in Nanjing University of Technology in China. He received Doctor Degree in China University of Mining & Technology in 1996. He currently works in Nanjing University of Technology as Ph.D. supervisor and vice president, and also is a member of National Safety Production Committee and a member of Fire Safety Association Academic Committee of China etc. He is author of four books, and more than 60 journal articles have been accepted in index of SCI/ EI.