Realization of Forest Internet of Things Using Wireless Network Communication Technology of Low-Power Wide-Area Network

This work implements an intelligent forest monitoring system using the Internet of things (IoT) with the wireless network communication technology of a low-power wide-area network (LPWAN), a long range (LoRa), and a narrow-band Internet of things (NB-IoT). A solar micro-weather station with LoRa-based sensors and communications was built to monitor the forest status and information such as the light intensity, air pressure, ultraviolet intensity, CO2, etc. Moreover, a multi-hop algorithm for the LoRa-based sensors and communications is proposed to solve the problem of long-distance communication without 3G/4G. For the forest without electricity, we installed solar panels to supply electricity for the sensors and other equipment. In order to avoid the problem of insufficient solar panels due to insufficient sunlight in the forest, we also connected each solar panel to a battery to store electricity. The experimental results show the implementation of the proposed method and its performance.

Next, we reviewed studies related to intelligent forest fire management. In [32][33][34], the authors proposed a forest fire detection system that randomly deployed sensor nodes in The rest of this work is organized as follows. Section 2 provides the background related to the forest sensors and communication technology proposed in Section 3. The proposed forest sensors and communication technology are presented in Section 3. Section 4 shows the implementation and experimental results. Section 5 gives a conclusion.

Background
In the past, the information collected by various monitoring equipment could be used through different wireless communication methods such as Zigbee, WiFi, 2G, 3G, or 4G. However, they were all limited by the transmission distance, power consumption, and transmission costs and could not be deployed in a large area, especially in a forest area. For long-distance, low-power, high-coverage wireless communication needs, the newly developed wireless network communication technology of an LPWAN in recent years can be roughly divided into two categories: an NB-IoT, which uses licensed frequency bands, and LoRa, Sigfox, and Weightless, which use unlicensed frequency bands. As shown in Figure 1, compared with other communication technologies, an LPWAN has many advantages, such as its long-distance range, high coverage, low power consumption, low cost, and so on. At present, the global Internet of things and communication manufacturers have actively set up various cross-domain or independent LPWAN base stations, combining their advantages of a long-distance range, high coverage, low power consumption, and low cost with related sensors and smart devices to provide related innovative services. In addition to the common characteristics of a long-distance range, low power consumption, and high coverage, this section evaluates and analyzes the advantages and disadvantages of the above-mentioned LPWAN communication technology and its application areas as follows: Thus, sensing data on parameters such as the light intensity, air pressure, ultraviolet intensity, and CO2 were transmitted successfully to a LoRa gateway connected to 3G/4G. Finally, the real-time sensing data were transmitted to a web server. The rest of this work is organized as follows. Section 2 provides the background related to the forest sensors and communication technology proposed in Section 3. The proposed forest sensors and communication technology are presented in Section 3. Section 4 shows the implementation and experimental results. Section 5 gives a conclusion.

Background
In the past, the information collected by various monitoring equipment could be used through different wireless communication methods such as Zigbee, WiFi, 2G, 3G, or 4G. However, they were all limited by the transmission distance, power consumption, and transmission costs and could not be deployed in a large area, especially in a forest area. For long-distance, low-power, high-coverage wireless communication needs, the newly developed wireless network communication technology of an LPWAN in recent years can be roughly divided into two categories: an NB-IoT, which uses licensed frequency bands, and LoRa, Sigfox, and Weightless, which use unlicensed frequency bands. As shown in Figure 1, compared with other communication technologies, an LPWAN has many advantages, such as its long-distance range, high coverage, low power consumption, low cost, and so on. At present, the global Internet of things and communication manufacturers have actively set up various cross-domain or independent LPWAN base stations, combining their advantages of a long-distance range, high coverage, low power consumption, and low cost with related sensors and smart devices to provide related innovative services. In addition to the common characteristics of a long-distance range, low power consumption, and high coverage, this section evaluates and analyzes the advantages and disadvantages of the above-mentioned LPWAN communication technology and its application areas as follows: NB-IoT: An NB-IoT is a carrier-grade network supported by the international telecommunications standards development organization, 3GPP, and built for the IoT. It has a good network transmission quality, high data security, and a low construction cost. Based on the low-rate IoT market in the licensed spectrum, an NB-IoT can be deployed directly on LTE networks, and an NB-IoT can be quickly deployed without drastically changing the current 4G LTE telecommunication network architecture. In addition, an NB-IoT can also be deployed through equipment upgrades based on the current operator's existing 2G, 3G, and 4G networks, which can reduce deployment costs. As a result, an NB-IoT is supported by telecom companies in various countries and is a widely used NB-IoT: An NB-IoT is a carrier-grade network supported by the international telecommunications standards development organization, 3GPP, and built for the IoT. It has a good network transmission quality, high data security, and a low construction cost. Based on the low-rate IoT market in the licensed spectrum, an NB-IoT can be deployed directly on LTE networks, and an NB-IoT can be quickly deployed without drastically changing the current 4G LTE telecommunication network architecture. In addition, an NB-IoT can also be deployed through equipment upgrades based on the current operator's existing 2G, 3G, and 4G networks, which can reduce deployment costs. As a result, an NB-IoT is supported by telecom companies in various countries and is a widely used Internet-of-things technology worldwide. The Global Mobile Suppliers Association announced in March 2019 that more than 100 operators have deployed an NB-IoT.
LoRa: LoRa is the basis of the wireless communication technology developed by the American semiconductor manufacturer Semtech through its acquisition of the French company Cycleo, with the specification completed in cooperation with IBM. The LoRa Weightless-N version adopts a sub-GHz license-free frequency band; the transmission rate is 30~100 kbit/s and the transmission distance is about 5 km. Weightless-W and Weightless-N only support one-way transmission, while the latest version, Weightless-P, supports two-way communication, and its transmission rate and transmission distance are about 100 kbit/s and up to 2 km, respectively.
As shown in Table 1, under the same conditions, LoRa has the best network signal coverage, but in terms of the number of supported nodes and spectrum efficiency, Weightless performs better than LoRa and Sigfox.

Related Work to Applications of LPWAN
In this sub-section, we summarize the current solutions based on similar networks in Section 2.1 for forests or environmental monitoring. In Refs. [43,44], data communication networks that can inform about forest fires in real-time were developed that could use longdistance, wireless-communication-based tools, namely LoRa. In terms of data transmission, the use of LoRa as an early warning method for monitoring forest fires in the Riau province allowed data to be sent from sensors to a gateway as far as 30 miles away [45]. In Ref. [46], M. I. Nashiruddin and S. Winalisa designed a LoRaWAN Internet-of-things network for Smart Manufacture on Batam Island. LoRa acquires high recognition by providing a low cost for IoT modules and equipment, M2M, and other industrial needs [47]. In order to monitor the system conditions perfectly, the authors of Ref. [48] incorporated LoRaWan- based IoT technology into the smart field environment. In Ref. [49], the authors applied IoT technology to propose a novel forestry management system in the Fushan Botanical Garden in Taiwan. Their system techniques included the following: 1. Transmission of sensing data on forest information using the wireless network communication technology of a low-power wide-area network (LPWAN) such as LoRa or an NB-IoT. 2. Application of different sensing techniques to process forest resources and monitor the microclimate changes in a forest. In Ref. [50], the authors presented the design and implementation of a LoRa-based forest-fire-monitoring system. The LoRa-based forest-fire-monitoring system technology was based on wireless technology that can transmit data across the forest. To detect the presence of a fire, Arduino Uno was used as a microcontroller that regulates the input from the AMG8833 sensor and GPS Ubox 6M. In Ref. [51], the authors built a LoRa-based smart agricultural management and monitoring system using a WSN in rural areas to replace the current technology of the agricultural monitoring system. In Ref. [52], the authors proposed the design and implementation of a LoRa-based wireless sensor network for monitoring the quality of water in coastal areas, rivers, and ditches with the aim of generating an observatory of water quality for the monitored areas. A comparison between the proposed solution with other methods is listed in Table 2.

Proposed Forest Sensors and Communication Technology
Based on the discussion in the last section, we adopted the two wireless network communication technologies LPWAN and NB-IoT, which use licensed frequency bands, and LoRa, which uses unlicensed frequency bands, combined with their respective sensors, as shown in Figure 2, to be the proposed forest sensors and communication technology. In forests or mountains, an NB-IoT is used in a small number of areas with 3G/4G telecommunication signals, while RoLa is used mostly in areas without 3G/4G telecommunication signals. The implementation architecture is presented in Sections 3.1 and 3.2.
[51] Reference [52] No The proposed method Yes Yes Yes Yes

Proposed Forest Sensors and Communication Technology
Based on the discussion in the last section, we adopted the two wireless network communication technologies LPWAN and NB-IoT, which use licensed frequency bands, and LoRa, which uses unlicensed frequency bands, combined with their respective sensors, as shown in Figure 2, to be the proposed forest sensors and communication technology. In forests or mountains, an NB-IoT is used in a small number of areas with 3G/4G telecommunication signals, while RoLa is used mostly in areas without 3G/4G telecommunication signals. The implementation architecture is presented in Sections 3.1 and 3.2.

NB-IoT Communication Technology and Its Respective Sensors
In a few areas with 3G/4G, we used NB-IoT communication technology to continuously return the sensing data from NB-IoT-support sensors to the server or computer through the 3G/4G telecommunication network. Figure 3 shows the proposed NB-IoTsupport sensors and the architecture of NB-IoT communication technology.

LoRa Communication Technology and Its Respective Sensors
In most areas without a 3G/4G telecommunication signal, the proposed LoRa signal repeat method will continuously return the sensing data of the LoRa-support solar microweather station. Figure 4 presents the proposed LoRa-support solar micro-weather station and the architecture of the LoRa signal repeat method, which is described in detail as follows. First, the gateway is set up in a place with electricity, such as a street lamp or public facility at the foot of a mountain, and is supplemented by an external battery that can be charged at any time to achieve uninterrupted power and avoid an unstable power supply in mountainous areas, as shown in Figure 5. Next, the LoRa-support solar micro-weather station is set up in a place that needs a forest resource survey or monitoring, and then the

NB-IoT Communication Technology and Its Respective Sensors
In a few areas with 3G/4G, we used NB-IoT communication technology to continuously return the sensing data from NB-IoT-support sensors to the server or computer through the 3G/4G telecommunication network. Figure 3 shows the proposed NB-IoTsupport sensors and the architecture of NB-IoT communication technology.

NB-IoT Communication Technology and Its Respective Sensors
In a few areas with 3G/4G, we used NB-IoT communication technology to continuously return the sensing data from NB-IoT-support sensors to the server or computer through the 3G/4G telecommunication network. Figure 3 shows the proposed NB-IoTsupport sensors and the architecture of NB-IoT communication technology.

LoRa Communication Technology and Its Respective Sensors
In most areas without a 3G/4G telecommunication signal, the proposed LoRa signal repeat method will continuously return the sensing data of the LoRa-support solar microweather station. Figure 4 presents the proposed LoRa-support solar micro-weather station and the architecture of the LoRa signal repeat method, which is described in detail as follows. First, the gateway is set up in a place with electricity, such as a street lamp or public facility at the foot of a mountain, and is supplemented by an external battery that can be charged at any time to achieve uninterrupted power and avoid an unstable power supply in mountainous areas, as shown in Figure 5. Next, the LoRa-support solar micro-weather

LoRa Communication Technology and Its Respective Sensors
In most areas without a 3G/4G telecommunication signal, the proposed LoRa signal repeat method will continuously return the sensing data of the LoRa-support solar microweather station. Figure 4 presents the proposed LoRa-support solar micro-weather station and the architecture of the LoRa signal repeat method, which is described in detail as follows. First, the gateway is set up in a place with electricity, such as a street lamp or public facility at the foot of a mountain, and is supplemented by an external battery that can be charged at any time to achieve uninterrupted power and avoid an unstable power supply in mountainous areas, as shown in Figure 5. Next, the LoRa-support solar micro-weather station is set up in a place that needs a forest resource survey or monitoring, and then the related sensing data are transmitted through LoRa communication technology. Whether the transmitted signal strength is sufficient to be received by the gateway is evaluated by the RSSI. The signal strength p d according to the distance (d) can be represented by: or: where p 0 is the strength of the transmission signal measured at a distance of one meter from the transmitter; d is the distance between the transmitter and receiver; and n is a signal attenuation constant that can be obtained from the received signal and the actual distance. Different levels of signal strength can reduce the location errors of the RSSI caused by the interferences. In order to determine the signal repeat location of a specified sensor, we defined the indication function by: where  denotes the threshold for which the receiver can receive the signal from the transmitter.
If the RSSI determines that the signal strength is not high enough to send the sensing data back to the gateway using (2) and (3), it is necessary to set up a RoLa signal repeat station powered by solar energy. Finally, the gateway sends the received sensing data back to the server or computer through the 3G/4G telecommunication network.

Experiments and Discussion
This section shows the implementation of the proposed forest monitoring system using the IoT with an LPWAN in the Fushan Botanical Garden in Taiwan. Section 4.1 shows the realization and experimental results of NB-IoT communication in a few areas with a 3G/4G telecommunication signal. Section 4.2 shows the realization and experimental results of LoRa repeat planning for a large area without a 3G/4G telecommunication signal.

Realization and Experimental Results of NB-IoT Communication
In a few areas with a 3G/4G telecommunication signal, as shown in Figure 6, we first set up the NB-IoT-support sensors and continuously sent out their sensing data by using NB-IoT communication technology. Next, the real-time sensing data, including Different levels of signal strength can reduce the location errors of the RSSI caused by the interferences. In order to determine the signal repeat location of a specified sensor, we defined the indication function by: where  denotes the threshold for which the receiver can receive the signal from the transmitter.
If the RSSI determines that the signal strength is not high enough to send the sensing data back to the gateway using (2) and (3), it is necessary to set up a RoLa signal repeat station powered by solar energy. Finally, the gateway sends the received sensing data back to the server or computer through the 3G/4G telecommunication network.

Experiments and Discussion
This section shows the implementation of the proposed forest monitoring system using the IoT with an LPWAN in the Fushan Botanical Garden in Taiwan. Section 4.1 shows the realization and experimental results of NB-IoT communication in a few areas with a 3G/4G telecommunication signal. Section 4.2 shows the realization and experimental results of LoRa repeat planning for a large area without a 3G/4G telecommunication signal.

Realization and Experimental Results of NB-IoT Communication
In a few areas with a 3G/4G telecommunication signal, as shown in Figure 6, we first set up the NB-IoT-support sensors and continuously sent out their sensing data by using NB-IoT communication technology. Next, the real-time sensing data, including Different levels of signal strength can reduce the location errors of the RSSI caused by the interferences. In order to determine the signal repeat location of a specified sensor, we defined the indication function by: where ε denotes the threshold for which the receiver can receive the signal from the transmitter. If the RSSI determines that the signal strength is not high enough to send the sensing data back to the gateway using (2) and (3), it is necessary to set up a RoLa signal repeat station powered by solar energy. Finally, the gateway sends the received sensing data back to the server or computer through the 3G/4G telecommunication network.

Experiments and Discussion
This section shows the implementation of the proposed forest monitoring system using the IoT with an LPWAN in the Fushan Botanical Garden in Taiwan. Section 4.1 shows the realization and experimental results of NB-IoT communication in a few areas with a 3G/4G telecommunication signal. Section 4.2 shows the realization and experimental results of LoRa repeat planning for a large area without a 3G/4G telecommunication signal.

Realization and Experimental Results of NB-IoT Communication
In a few areas with a 3G/4G telecommunication signal, as shown in Figure 6, we first set up the NB-IoT-support sensors and continuously sent out their sensing data by using NB-IoT communication technology. Next, the real-time sensing data, including temperature and humidity, were connected to the 3G/4G telecommunication network, and finally, they were transmitted to the web server, as shown in Figure 7. temperature and humidity, were connected to the 3G/4G telecommunication network, and finally, they were transmitted to the web server, as shown in Figure 7.

Realization and Experimental Results of LoRa Repeat Planning for Solving No Signal
To transmit sensing data in the large areas without a 3G/4G telecommunication signal, as shown in Figure 8, we first assembled a LoRa-support solar micro-weather station with LoRa communication, an illuminance sensor, an atmospheric pressure sensor, an ultraviolet light sensor, a carbon dioxide sensor, etc. The antenna was 868 megaHz. For convenience, the RSSI values were measured by the tool WifiInfoView. Then, we used the RSSI to measure the signal strength and set up a gateway on the beam of the pavilion at the entrance of the Fushan Botanical Garden, which has both electricity and 3G/4G internet signals. The gateway shared the electricity of the pavilion lights and monitors. In order to avoid an unstable power supply in mountainous areas, the gateway was supplemented by 7A batteries that can be charged at any time to achieve uninterrupted power. Next, we set up a LoRa-support solar micro-weather station near the top of the mountain where we needed to conduct a resource investigation. Thus, the LoRa-support solar micro-weather station could continuously send out sensing data by using LoRa communication technology.

Realization and Experimental Results of LoRa Repeat Planning for Solving No Signal
To transmit sensing data in the large areas without a 3G/4G telecommunication signal, as shown in Figure 8, we first assembled a LoRa-support solar micro-weather station with LoRa communication, an illuminance sensor, an atmospheric pressure sensor, an ultraviolet light sensor, a carbon dioxide sensor, etc. The antenna was 868 megaHz. For convenience, the RSSI values were measured by the tool WifiInfoView. Then, we used the RSSI to measure the signal strength and set up a gateway on the beam of the pavilion at the entrance of the Fushan Botanical Garden, which has both electricity and 3G/4G internet signals. The gateway shared the electricity of the pavilion lights and monitors. In order to avoid an unstable power supply in mountainous areas, the gateway was supplemented by 7A batteries that can be charged at any time to achieve uninterrupted power. Next, we set up a LoRa-support solar micro-weather station near the top of the mountain where we needed to conduct a resource investigation. Thus, the LoRa-support solar micro-weather station could continuously send out sensing data by using LoRa communication technology. However, as shown in Figure 9, at a distance of between 775 m and 1645 m from the LoRa-support solar micro-weather station, that is, from 810 m above sea level to 680 m, the signal was lost for an RSSI of −120 dB and was unstable from −110 dB to 120 dB. Therefore, as shown in Figure 10, we initially set up a LoRa repeat station between the LoRasupport solar micro-weather station and the gateway to solve the lost-signal problem so as to successfully repeat the real-time sensing data, including data on the illuminance, atmospheric pressure, ultraviolet light, and carbon dioxide. As shown in Table 3, we evaluated the correspondence between the distance and the signal strength using three times the average of the RSSI from the LoRa-support solar micro-weather station on the mountain slope without rain. In order to reduce the location errors of the RSSI from −110 dB to 120 dB caused by the interference, we excluded the RSSIs below −110 dB, and Equation (3) became: However, as shown in Figure 9, at a distance of between 775 m and 1645 m from the LoRa-support solar micro-weather station, that is, from 810 m above sea level to 680 m, the signal was lost for an RSSI of −120 dB and was unstable from −110 dB to 120 dB. Therefore, as shown in Figure 10, we initially set up a LoRa repeat station between the LoRa-support solar micro-weather station and the gateway to solve the lost-signal problem so as to successfully repeat the real-time sensing data, including data on the illuminance, atmospheric pressure, ultraviolet light, and carbon dioxide. As shown in Table 3, we evaluated the correspondence between the distance and the signal strength using three times the average of the RSSI from the LoRa-support solar micro-weather station on the mountain slope without rain. In order to reduce the location errors of the RSSI from −110 dB to 120 dB caused by the interference, we excluded the RSSIs below −110 dB, and Equation (3) became: I(d) = 1, if d ≥ 500 0, otherwise where ε = 500 m or ε = 0.5 km. Then, the sensing data were transmitted to the LoRa gateway, which was connected to the 3G/4G telecommunication network with an average of 10 s. Finally, these real-time sensing (the sensor senses immediately) data were transmitted to a web server within seconds.   evaluated the correspondence between the distance and the signal strength using three times the average of the RSSI from the LoRa-support solar micro-weather station at the mountain edge without rain in Table 5. Because of the attenuated 20% due to heavy rain we set up a signal repeat station every 1 km along the mountain edge. Finally, Figure 13 shows the realization of multiple LoRa-support solar micro-weather stations with repea stations and communication technology.    repeat station every 0.4 km between the LoRa-support solar micro-weather station and the gateway on the mountain slope. Therefore, we added an additional signal repeat station between the weather station and the original signal repeat station, as shown in Figure 11, to obtain all sensing data in the web server again, as shown in Figure 12. Similarly, we evaluated the correspondence between the distance and the signal strength using three times the average of the RSSI from the LoRa-support solar micro-weather station at the mountain edge without rain in Table 5. Because of the attenuated 20% due to heavy rain, we set up a signal repeat station every 1 km along the mountain edge. Finally, Figure 13 shows the realization of multiple LoRa-support solar micro-weather stations with repeat stations and communication technology.

Conclusions
In this work, we applied the wireless network communication technology of an LPWAN to implement an intelligent forest Internet-of-things (IoT) management by taking the Fushan Botanical Garden in Taiwan as a real case. In the areas with 3G/4G, we set up NB-IoT-support sensors and continuously sent out their sensing data by using NB-IoT communication technology. In particular, an RSSI multi-hop for the signal repeat of the LoRa-support sensors was proposed to solve the problem of long-distance communication without 3G/4G. For the forest without electricity, we installed solar panels to supply electricity to the sensors and other equipment so that the sensing data on parameters such as light intensity, air pressure, ultraviolet intensity, and CO 2 would be transmitted to the LoRa gateway. By connecting the LoRa gateway to 3G/4G, the real-time sensing data were successfully transmitted to the web server. In order to avoid the problem of insufficient solar panels due to insufficient sunlight in the forest, we also connected each solar panel to a battery to store electricity.
In the future, we will design a more comprehensive mathematical model that considers the location, number, and cost of weather stations, sensors, relay stations, gateways, and other equipment.