## 1 Introduction  
In recent years, the concept of the Internet of things (IoT) has developed rapidly and has been applied successfully in different fields, including city applications [1; 2; 3; 4; 5; 6; 7; 8], medical applications [9; 10; 11; 12; 13; 14; 15; 16; 17; 18], industrial applications [19; 20; 21; 22], agricultural applications [23; 24; 25; 26; 27], and forestry applications [28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43]. The applications using IoT technology in forestry can be classified into three major aspects: forest resource planning and environmental monitoring, the intelligent management of forest fires, and the prevention of illegal logging. Forestry IoT technology has been successfully applied to forest resource planning and environmental monitoring using a wireless sensing network (WSN). [PERSON] et al. [28] proposed a platform of forest environmental factor collection based on the ZigBee protocol. The platform includes many different types of terminal monitoring equipment such as temperature, humidity, water level, gas, micro-electromechanical system (MEMS), photoresistor, and human infrared sensors. [PERSON] and [PERSON] [29] discussed the WSN-based landslide forecasting and geographical information system as an overview. [PERSON] et al. [30] used available resources to present an effective WSN architecture with a solution. In the WSN architecture, they tried to optimize the duty cycle of a single sensor (but a single node) or maximize the network service life. [PERSON] et al. [31] proposed an IoT-based environmental monitoring system using a WSN. 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 forest area, with each node being equipped with a temperature sensor. Moreover, each node checked the environment periodically to determine whether there was an emergency. When some sensor nodes detect a significant change in temperature, they will broadcast data packets containing the measured values. At the same time, the measured values are presented on computer web pages and mobile phone pages. Generally speaking, the higher the sensor density, the more reliable the data obtained. However, saving energy is also one of the important issues in WSNs. There is a compromise between the two. Therefore, [PERSON] et al. [35] proposed a mathematical solution called the forest fire monitoring paradigm (FFMP). The purpose of the FFMP is to provide early detection and location information for forest fires based on a hybrid WSN. Differently from pure static and mobile WSNs, an FFMP hybrid WSN is composed of mobile sensor nodes and static sensor nodes. Hybrid wireless sensor networks are a compromise between cost and coverage. The system proposed by [PERSON] et al. [36] consists of temperature sensors and a GSM module, where the temperature sensors use tree power for their operation and the GSM module is connected to the GSM network to transmit the detected fire alarm signal. In illegal logging prevention, the sensor network by [PERSON] et al. [37], which uses sound collection and actual recording, is the first anti-pilot logging system that can continuously provide real-time monitoring for endangered forests. [PERSON] and [PERSON] [38] recorded the sound through a microphone and loaded the sound into matlab software on the network to perform a Fourier transform operation to transform the time domain into the frequency domain for analysis and recognition. [PERSON] [39] developed a system that can be used to stop smuggling. Each tree is equipped with a small electronic device composed of a microcontroller, a flexible vibration sensor, and a Zigbee module. The flexible vibration sensor detects tree cutting and the communication is completed by the Zigbee, GSM-modem, CMGF-message-format module.