An Intelligent Wireless System for Field Ecology Monitoring and Forest Fire Warning

Abstract

Based on Internet-of-Things and multi-sensor technology, an intelligent wireless monitoring system was developed to obtain field ecological parameters and provide forest fire warning in real-time. The GPRS and China’s Beidou satellite communication were selectively used for date transmission in the field with weak cell phone signals. This monitoring system is mainly composed of several field ecological monitoring stations, a cloud server, and online system software. Atmosphere, soil, sunlight and plant parameters of different regions are obtained real-time by sensors stably and reliably. This system has functions such as field ecological data storage, dynamic query, report generation, and data analysis. As an example of typical application, the forest fire weather grade, which was supplemented with the litter layer soil humidity, was calculated to realize the early warning of the local forest fire in this system through continuous experiments at Beijing Jiufeng National Forest Park from March to May 2017 and Inner Mongolia from March to June 2018. The success ratios of data transmission through Beidou satellite were 98.57%, 99.43%, 99.59%, and 98.85%, respectively, in Beijing, and through GPRS were 99.89% and 99.90% in Inner Mongolia. Long-term real-time field ecological monitoring and forest fire warning were successfully realized. This system can be widely used for big data field acquisition and analysis in forest and agriculture regions.

GIS-Based Forest Fire Susceptibility Zonation with IoT Sensor Network Support, Case Study—Nature Park Golija, Serbia

“…Additionally, a combination of temperature and carbon monoxide measurements is used in a simple forest fire detection system [ 84 ] with the predefined decision criteria. Finally, a very complex solution in which soil parameters (soil temperature, soil moisture), air parameters (air temperature, air moisture, carbon dioxide concentration, wind direction, wind speed, precipitation, negative oxygen ion, PM 2.5), light parameters (global radiation, light intensity, sunshine hours threshold, photo synthetically active radiation), and plant parameters (needle-type stem moisture, non-destructive stem moisture) is used for forest fire prediction [ 85 ]. …”

Marine Cold Chain Transportation Monitoring and Route Scheduling Optimization Based on IoV-BDS

“…INMARSAT system can carry out seamless communication in the world [15], [16], but its high communication cost brings great resistance to cost-saving seaborne transportation. BDS is capable of providing positioning and navigation, two-way communication, and precise timing service anytime and anywhere within the coverage area [17], these functions make BDS not only work as GPS but also work as an INMARSAT system to realize maritime communication [18]. Existing studies have evaluated the progress and performance of BDS [19]- [21] and applied to many scenarios, such as precise positioning [22], [21], fire warning [23], smart grid [24], emergency rescue [25], [26], environment monitoring [27], [28].…”

“…. We construct the X by formula (17), it represents a set of ports, and the remaining catches in the ship could meet requirement of any ports in X .…”

“…When q 1 ≤ q 0 , the port with minimum cost is directly selected to be the next port; when q 1 ≥ q 0 , the state transition probability is selected based on the roulette. The q 0 has a great influence on the final solution if q 0 is set as a fixed value, it should be adjusted in equation (23) to improve solution efficiency.…”

Renovation of Automation System Based on Industrial Internet of Things: A Case Study of a Sewage Treatment Plant

“…The traditional industrial control field adopts the distributed control system, whose server is built by the local servers, and transmits the data to PLC through the bus or Ethernet for analysis and processing. With the arrival of the era of big data and the rapid development of cloud platform technology, traditional SCADA has difficulty processing the massive data and realizing remote storage, while the cloud platform technology is able to store data remotely and has a powerful data processing function, which is applicable to the IIoT [32]. At present, there are many enterprises providing cloud platform technology on the market, such as Alibaba cloud, Tencent cloud and Baidu cloud.…”