Design of water quality monitoring system for aquaculture ponds based on NB-IoT

Abstract

In order to promote the development of aquaculture informatization and monitor aquaculture ponds more accurately and conveniently, this article has developed a water quality monitoring system for aquaculture ponds based on the narrow band internet of things (NB-IoT) technology. This system realizes remote collection and data storage of multi-sensor processor information (temperature, pH, dissolved oxygen (DO) and other environmental parameters), as well as intelligent control and centralized management of breeding ponds. The system uses STM32L151C8 microcontroller and sensor terminal real-time acquisition, such as temperature, pH value, dissolved oxygen. It realizes data aggregation and transmission over a long distance to the Internet of things (IoT) telecom cloud platform through the technology of NB-IoT. The software called Keil implement the data format design of wireless communication module and data transmission. Java is used to develop background monitoring applications for accessing cloud platform, controlling underlying devices and local data processing. It can not only send hypertext transfer protocol (HTTP) requests to monitor cloud platform data, but also issue commands to the underlying control module to control the startup and shutdown of equipment such as aerator. The system was implemented and tested in ChangZhou, JiangSu Province, China. The experimental results showed that the system can obtain water quality parameters in time. The temperature control accuracy is maintained at ±0.12℃, the average relative error is 0.15 %, the dissolved oxygen control accuracy is maintained within ±0.55mg/L, the average relative error is 2.48 %, the pH control accuracy is maintained at ±0.09, and the average relative error is 0.21 %. The system has stable overall operation, real-time and accurate data transmission, which can meet the actual production needs and provide strong data and technical support for further water quality regulation and aquaculture production management.

Introduction

With the rapid development of aquaculture industry in various countries, water factors in the water quality environment, such as temperature, pH and dissolved oxygen (DO), are becoming more and more important (Li and Yang, 2018). They are not only the basis for the survival of aquatic animals, but also the key factors affecting water quality. Therefore, monitoring of water quality timely is of great practical significance to aquaculture for high yield, health and safety.

Researchers have conducted research on aquaculture environmental monitoring in recent years. Wang et al. (2012) designed the ocean remote monitoring system. Nam et al. (2015) deployed wireless sensor networks (WSN) in aquaculture farms by combining ZigBee and code division multiple access (CDMA) technologies to monitor the environmental information of offshore fish species (Rawat et al., 2013). Chen et al. (2016) established the WSN automatic monitoring system for fishery environment by combining ZigBee and WiFi. Schmidt et al. (2018) designed an autonomous buoy system for coastal aquaculture and water quality monitoring. Lorena et al. (2018) combined WSN and general packet radio service (GPRS) to remotely monitor water quality parameters and feed consumption in fish breeding bases. The above aquaculture monitoring systems have their own characteristics, but with the development of the Internet of things technology, in recent years, the emergence of equipment access oriented low power wan. A typical example is Narrow Band Internet of Things (NB-IoT), its single-hop distance can be up to thousands of meters, which is more suitable for parks, breeding ponds and other places in terms of node communication range, node deployment number and environmental applicability. In a short period of two years, NB-IoT is taking root in various fields of life, such as intelligent parking, intelligent street lights, shared bicycles, intelligent manhole covers, remote meter reading, intelligent buildings and so on. Zhang et al. (2018a, 2018b) proposed an architecture based on NB-IoT to connect intelligent hospital equipment, and introduced edge computing to deal with delay requirements in medical process. Wang and Yang (2018) designed a smart street light management system based on solar street light with good stability and broad application prospect by adopting multi-layer distributed structure and NB-IoT network. Cao and Li (2018) proposed a data acquisition scheme for the Internet of vehicles based on NB-IoT transformation, and deployed and analyzed the network structure. Zhang et al. (2018a, 2018b) designed a low-power information monitoring system by adopting NB-IoT communication technology, the long range (LoRa) communication technology and least recently used (LRU) algorithm. Jia et al. (2017) proposed an intelligent manhole cover management system for smart city based on edge computing, with high application efficiency. He et al. (2018) developed a set of intelligent greenhouse environmental automatic regulation system based on the early-stage technology of 5 G low-power mass connection scene by taking advantage of the strong penetration and wide coverage of this technology. Anand and Regi (2018) uses NB-IoT to remotely monitor water levels in tanks. Lv and Zhao (2018) designed a temperature acquisition system that uses low-power single-chip microcomputer as processor and combines NB-IoT communication module for wireless transmission. Chen (2018) designed a new temperature monitoring system for electroplating production line, which has good regulatory performance. In order to effectively solve the current problems of insufficient coverage of aquaculture regional network, excessive terminal power consumption, a large number of terminal equipment and high comprehensive cost, this paper selects NB-IoT to be applied in aquaculture pond monitoring, which is based on the cellular network. Direct access to cellular network can greatly simplify the network structure, and reduce the difficulty of deployment and maintenance. The technology simultaneously have achieved low cost, low power consumption, wide coverage and large connection, which is very suitable for aquaculture industry like low frequency, small data packet and communication delay insensitive the Internet of things (IoT) business. Low-cost and low-power mobile terminals be distributed in each breeding base through the connection between NB-IoT and sensors, it is will provide guarantee for aquaculture production and research on the IoT.

Considering the advantages of this technology in the application to the aquaculture industry and the current development trend, this paper designed and realized the aquaculture pond water quality monitoring system based on NB-IoT, which uses STM32L151C8 chip and sensor technology to collect aquatic environment information, and implements the non-gateway data report through the Narrow Band (NB) module. The cloud platform saves immediately after receiving the data or issuing the command, and it is ready to parse and send the protocol package at any time. On the one hand, the system can monitor the aquaculture environment in real time and send relevant data through the IoT platform to Personal Computer (PC) and remote clients. On the other hand, it can control the work of the underlying module by issuing a command, coordinate each sensor node and configure a credible module, periodically detect the credibility of each node, so as to ensure the integrity and security of the sensor node (Shetty et al., 2018). The results provide reference for further water quality regulation and aquaculture production management.

The system consists of four layers: perception layer, transport layer, platform layer and application layer. The perception layer is deployed in the pond, which is responsible for the data collection and aerator control of the aquaculture tank. The transport layer mainly contains the core network and the communication base station, which is responsible for the transmission of business data. The platform layer saves the business data and monitors the system in real time. The application layer controls the opening and closing of the bottom module and the aerator.

The rest of this paper is organized as follows: Section 2 introduces the hierarchical structure of the system and the two functions it implements. Section 3 mainly describes the design of the hardware part of the perception layer. Section 4 presents the transport layer network and topology diagram. Section 5 discusses the design of the platform layer. Section 6 is about the design of the software part of the application layer. Section 7 gives results and data monitored, and finally, Section 8 concludes the article.