An intelligent IoT emergency vehicle warning system using RFID and Wi-Fi technologies for emergency medical services

Abstract

BACKGROUND:

Collisions between emergency vehicles for emergency medical services (EMS) and public road users have been a serious problem, impacting on the safety of road users, emergency medical technicians (EMTs), and the patients on board.

OBJECTIVE:

The aim of this study is to develop a novel intelligent emergency vehicle warning system for EMS applications.

METHODS:

The intelligent emergency vehicle warning system is developed by Internet of Things (IoT), radio-frequency identification (RFID), and Wi-Fi technologies.

RESULTS:

The system consists of three major parts: a system trigger tag, an RFID system in an emergency vehicle, and an RFID system at an intersection. The RFID system either in an emergency vehicle or at an intersection contains a controller, an ultrahigh-frequency (UHF) RFID reader module, a Wi-Fi module, and a 2.4-GHz antenna. In addition, a UHF ID antenna is especially designed for the RFID system in an emergency vehicle. The IoT system provides real-time visual warning at an intersection and siren warning from an emergency vehicle in order to effectively inform road users about an emergency vehicle approaching.

CONCLUSION:

The developed intelligent IoT emergency vehicle warning system demonstrates the capabilities of real-time visual and siren warnings for EMS safety.

Keywords

Emergency medical service (EMS)emergency vehicle Internet of Things (IoT)radio-frequency identification (RFID)Wi-Fi

1. Introduction

Emergency medical services (EMS) provide transportation for people who need urgent medical care. Collisions between emergency vehicles and public road users have been a universal problem for all EMS throughout the world. Regardless of the country, this remains an issue. For instance, 114 firefighters were killed in the line of duty in Taiwan from 1952 to 2015. Among them, 24 were due to traffic accidents which accounted for 21%. The United States is also confronting the same problem. Multi-Discipline Response and Roadway Safety reported that the second main cause of death among firefighters was traffic accidents [1]. Traffic accidents of emergency vehicles have a serious impact on the safety of not only road users but also emergency medical technicians (EMTs) as well as the patients on board, who are under EMTs’ care. More than half of the collisions occur at intersections, especially when the emergency vehicles are trying to proceed through red lights [2]. When traffic accidents of emergency vehicles occurred, many road users claimed that they had not heard a siren. A study revealed that the distance for motorists to accurately localize the ambulance is only 25 m [3]. Also, the U.S Department of Transportation reported that the maximal siren effective distance is only 8–12 m due to the signal attenuation [4]. These facts verify that public road users have a difficult time to hear sirens and localize the approaching emergency vehicle. The current siren warning of ambulances may not be efficient enough for safeguarding the safety of the public.

Most ambulance crashes occurred during emergency use and at intersections. An analysis of ambulance crash data reported by The Fire Protection Research Foundation in 2011 also revealed that 58.23% of the ambulance crashes occurred during emergency use [5]. In addition, some statistics showed that most crashes between emergency vehicles and motorists occurred at intersections [6]. These statistics are consistent, and indicate that intersections are the most dangerous areas for emergency vehicles and motorists due to the ineffectiveness of sirens.

A few approaches have been suggested to prevent emergency vehicle crashes, for instance, by means of installing a louder siren or an emergency vehicle preemption (EVP) system [7]. However, as the modern vehicles provide excellent noise reduction, a louder siren may not be the required solution. The potential disadvantage of the EVP system is that emergency vehicles may have to stop at each intersection to wait for motorists to clear due to the signal congestion at downstream intersections caused by peak traffic hour. In addition, the overall installation budget of the EVP system is relatively high for full implementation; as a result, it will decrease the effectiveness. As mentioned above, the collisions tend to occur in urban areas; this correlates with the heavy traffic and high population density. The traffic lights in urban areas are very intensive in most large cities around the world. Therefore, the EVP system may not be the only excellent solution. An easy installation and cost effective approach to prevent emergency vehicle crashes is crucial for all emergency departments and organizations.

The Internet of Things (IoT) technology provides the networking between objects in one form or another [8, 9, 10]. Radio-frequency identification (RFID) [11, 12, 13, 14, 15, 16, 17, 18] is a successful wireless communication technology to meet the IoT paradigm. A unique identification (ID) code is stored in an electronic tag, which is attached to objects, and is read by a reader via radio-frequency (RF) signals. RFID technology has been widely applied in various fields, such as location tracking, manufacturing, logistics, supply chain management, and health care [16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28].

In this paper, a novel intelligent IoT emergency vehicle warning system for EMS is proposed using RFID technology in order to avoid the traffic accidents of emergency vehicles. In the system, the visual emergency vehicle warning signs made by light-emitting diodes (LEDs) are installed in conjunction with traffic lights at intersections so that road users can easily see the emergency vehicle warning when emergency vehicles approach. The IoT system provides the features of real-time visual and siren emergency vehicle warnings for EMS applications.

Figure 1.

Analysis of reasons for ambulance crashes.

2. Ambulance crash analysis

A 2011–2015 five-year retrospective ambulance crash analysis is conducted based on the data of the Changhua County Fire Bureau, Taiwan. Figure 1 depicts the analysis of the reasons for ambulance crashes; there are 56 ambulance crashes in total. Ambulance collisions with motorists at intersections while trying to proceed through red lights account for 48%.

Figure 2.

EMS call volume versus ambulance crash number.

Figure 2 shows the EMS call volume versus the ambulance crash number. Despite the EMS call volume increasing every year, the ambulance crash rate has remained steady. Figure 3 illustrates the analysis of ambulance crash hours The majority of collisions occur at heavy traffic hours, 1600 to 2000 (29%) and 0800 to 1200 (27%). In addition, the most collisions occur in urban areas. It indicates that the ambulance collisions correlate with the heavy traffic and high population density.

Figure 3.

Analysis of ambulance crash hours.

Figure 4.

Emergency vehicles: (a) ambulance and (b) ladder truck.

Figure 5.

Operation scheme of intelligent IoT emergency vehicle warning system.

Figure 6.

Structure of RFID system in emergency vehicle.

3. System design

The intelligent IoT emergency vehicle warning system integrates the visual warning at an intersection with the siren warning from an emergency vehicle for effectively attracting the road users’ attention about the approaching emergency vehicle. Figure 4 shows typical emergency vehicles, an ambulance and a ladder truck. The operation scheme of the intelligent IoT emergency vehicle warning system is shown in Fig. 5. The intelligent IoT emergency vehicle warning system comprises three major parts. The first part is a system trigger tag on a utility pole about 300 m from an intersection. The system trigger tag is a remote passive electronic sensor tag. The second part is the RFID system in an emergency vehicle, which includes a controller, an ultrahigh-frequency (UHF) RFID reader module, a UHF ID antenna, a Wi-Fi module, and a 2.4-GHz antenna, as shown in Fig. 6. The controller communicates with the UHF RFID reader module through a universal asynchronous receiver/transmitter (UART) interface and with the Wi-Fi module through an Ethernet interface. The third part involves the RFID system at an intersection; it includes a controller, a UHF RFID reader module, a UHF antenna, a Wi-Fi module, a 2.4-GHz antenna, and an LED module, as shown in Fig. 7. The RFID system at an intersection not only has a similar structure to the RFID system in an emergency vehicle, but also includes an additional LED module which is installed in conjunction with traffic lights at intersections. The controller of the RFID system at an intersection communicates with the LED module through a general-purpose input/output (GPIO) interface. The LED module provides LED emergency vehicle warning signs to the road users. In addition to the siren warning from an emergency vehicle, the LED visual emergency vehicle warning at an intersection can make the road users pay more attention to the approaching emergency vehicle.

Figure 7.

Structure of RFID system at intersection.

The system operation steps:

•

Step 1: The dispatch center dispatches an emergency vehicle to the incident site.

•

Step 2: The RFID system in an emergency vehicle is activated. The operation flow of the RFID system in an emergency vehicle is shown in Fig. 8 and described as follows:

Figure 8.

Operation flow of RFID system in emergency vehicle.

•

Step 2-1: The UHF RFID reader module is activated in order to read the ID of the system trigger tag installed on a utility pole.

•

Step 2-2: After reading the trigger tag ID, the controller calculates a computer command key and then activates the Wi-Fi module of the RFID system in an emergency vehicle.

•

Step 2-3: After the Wi-Fi module of the RFID system in an emergency vehicle is activated, it will automatically search the Wi-Fi module of the RFID system at an intersection. The Wi-Fi wireless communication between the RFID systems in an emergency vehicle and at an intersection is then established.

•

Step 2-4: The RFID system in an emergency vehicle sends a computer command key to the RFID system at an intersection.

•

Step 3: The operation flow of the RFID system at an intersection is shown in Fig. 9 and described as follows:

Figure 9.

Operation flow of RFID system at intersection.

•

Step 3-1: The Wi-Fi module of the RFID system at an intersection is waiting for the wireless communication search and the computer command key from the Wi-Fi module of the RFID system in an emergency vehicle.

•

Step 3-2: After the wireless communication between the RFID systems at an intersection and in an emergency vehicle is connected, the RFID system at an intersection receives a computer command key issued from the RFID system in an emergency vehicle.

•

Step 3-3: The computer command key is decrypted and verified.

•

Step 3-4: After the command legitimacy is confirmed, the LED module is activated and the LED warning signs are turned on. The LED light functions as a warning signal to the road users when the emergency vehicle approaches an intersection.

•

Step 3-5: The UHF RFID module of the RFID system at an intersection is activated. A certain time frame involves a countdown.

•

Step 3-6: If the ID antenna of the RFID system in an emergency vehicle is read by the UHF RFID module of the RFID system at an intersection during the countdown in a time frame, the LED module will be immediately turned off. On the other hand, if the ID antenna of the RFID system in an emergency vehicle is not read during the countdown in a time frame, the LED module will be turned off after the countdown.

4. Design of trigger tag antenna

The UHF RFID tag integrated circuit (IC) adopted in the system trigger tag is Alien Higgs-2. The equivalent circuit diagram of the Alien Higgs-2 RFID tag IC is shown in Fig. 10. The impedance of the RFID tag IC is calculated as $Z_{ic}=$ 11 – $j$ 131 ohms.

Figure 10.

Equivalent circuit diagram of Alien Higgs-2 RFID tag IC.

In this paper, the antenna design and the radiation pattern simulation are based on ANSYS HFSS, a high-frequency electromagnetic field simulator. A capacitive antenna is designed considering the system trigger tag is attached to the utility pole made from cement. The layout of the antenna of the system trigger tag is shown in Fig. 11. The size of the antenna is 80 mm (L) $\times$ 15 mm (W) $\times$ 0.035 mm (H) and a lump port feeding is utilized.

Figure 11.

Layout of trigger tag antenna.

Figure 12.

Impedance characteristics of trigger tag antenna.

Figure 12 shows the impedance characteristics of the trigger tag antenna. The impedance of the antenna at an operation frequency of 900 MHz is $Z_{ant}=$ 8 $+$ $j$ 156 ohms. The impedance of the antenna at 925 MHz is $Z_{ant}=$ 11 $+$ $j$ 168 ohms. The antenna power transmission coefficient $\tau$ is calculated from $Z_{ic}$ and $Z_{ant}$ in accordance with Eq. (1) and the farthest reading distance $R_{\textit{read}}$ is then calculated by Eq. (2), as follows:

$\tau=\frac{\left({{4}\cdot R_{ic}\cdot R_{ant}}\right)}{\left({\left|{Z_{ant}+% Z_{ic}}\right|}\right)^{2}},$ (1)

$R_{\textit{read}}=\left({\frac{\lambda}{4\pi}}\right)\cdot\left({\textit{EIRP}% \cdot\frac{G_{\textit{tag}}\cdot\tau}{P_{s}}}\right)^{\frac{1}{2}},$ (2)

where $\lambda$ is the wavelength of the antenna operation frequency, EIRP is the equivalent isotropically radiated power, $P_{s}$ is the minimum excitation power of the RFID tag IC, and $G_{\textit{tag}}$ is the gain of the trigger tag antenna.

Figure 13 shows the three-dimensional (3D) radiation pattern diagram of the trigger tag antenna. The antenna of the system trigger tag exhibits a donut-like radiation pattern. The maximum antenna gain is 1.656 dB at an operation frequency of 920 MHz.

Figure 13.

Radiation pattern of trigger tag antenna.

5. Design of ID antenna

The ID antenna installed in an emergency vehicle is a novel antenna design. The main function of the ID antenna is to read the system trigger tag on a utility pole and provide its own identification code for the reading of the RFID systems at intersections.

Figure 14.

Equivalent circuit of ID antenna.

Figure 14 shows the equivalent circuit diagram of the ID antenna with an RFID tag IC. The ID antenna consists of a radiator and a matching circuit. By utilizing the inductive coupling characteristics, the RF energy is captured to activate the RFID tag IC. The ID antenna transforms high frequency current energy into space electromagnetic energy for radiation. A coupled matching circuit is in the ID antenna. The inductively coupled matching circuit and the radiator are two individual structures. The energy transmission between the two structures is carried out by the inductive coupling. The gap between the two structures affects the magnetic coupling strength. This design is cost effective and space saving.

Figure 15.

Layout of matching circuit of ID antenna.

Figure 15 shows the layout of the ID antenna. The gap width is 3 mm and it is the feeding point of an RFID tag IC. The mutual effect between the radiator and the matching circuit depends on the self inductance of the matching circuit, $L_{m}$ . The impedance of the matching circuit $Z_{m}$ , can be calculated by

$\displaystyle Z_{m}=j\omega L_{m},$ (3)

where $\omega$ is the angular frequency.

The impedance of the RFID tag IC, $Z_{t}$ , is determined by

$Z_{t}=Z_{m}+\frac{\left({2\omega M_{i}}\right)^{2}}{Z_{r}},$ (4)

where $Z_{r}$ is the impedance of the radiator and $M_{i}$ is the mutual inductance between the radiator and the matching circuit.

Figure 16.

Top view of ID antenna.

Figure 16 shows the top view of the ID antenna. A 0.2-mm-thick PCB substrate is utilized. The size of the single side of the radiator is 70 mm (L) $\times$ 2 mm (W) $\times$ 0.035 mm (H).

Figure 17.

Impedance characteristics of ID antenna.

Figure 17 shows the impedance characteristics of the ID antenna. The antenna impedance is $Z_{\textit{ant}}=$ 50 – $j$ 35 ohms at an operation frequency of 900 MHz.

Figure 18.

Radiation pattern of ID antenna.

Figure 18 shows the 3D radiation pattern of the ID antenna. The gain of the antenna is 2.416 dB at an operation frequency of 900 MHz.

6. Conclusions

In this study, a novel intelligent IoT emergency vehicle warning system is developed for the EMS. The IoT system contains a system trigger tag, an RFID system in an emergency vehicle, and an RFID system at an intersection. The wireless communication in the system utilizes UHF RFID and Wi-Fi technologies. The system demonstrates the functions of real-time visual and siren emergency vehicle warnings. The road users easily become aware of the approaching emergency vehicles. The intelligent IoT emergency vehicle warning system exhibits great potential for EMS applications.

Footnotes

Acknowledgments

This work was supported in part by the Ministry of Science and Technology of Taiwan, R.O.C. under Contracts MOST 106-2218-E-018-002, MOST 106-2218-E-018-003, and MOST 104-2221-E-018-016. The authors thank the Changhua County Fire Bureau for providing ambulance crash information.

Conflict of interest

None to report.

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