Daoliang Li

Design and Development of Water Quality Monitoring System Based on Wireless Sensor Network in Aquaculture

This paper presents a system framework taking the advantages of the WSN for the real-time monitoring on the water quality in aquaculture. We design the structure of the wireless sensor network to collect and continuously transmit data to the monitoring software. Then we accomplish the configuration model in the software that enhances the reuse and facility of the monitoring project. Moreover, the monitoring software developed to represent the monitoring hardware and data visualization, and analyze the data with expert knowledge to implement the auto control. The monitoring system has been realization of the digital, intelligent, and effectively ensures the quality of aquaculture water. Practical deployment results are to show the system reliability and real-time characteristics, and to display good effect on environmental monitoring of water quality.

AN EARLY WARNING SYSTEM FOR FLOUNDER DISEASE

With the constant expansion of the scale and mismanagement in aquaculture,the diseases of flounder occur more and more frequently than before, which has brought great economic losses to fish farmers. For the sake of the problem described above, based on a great number of surveys, the early warning theory of flounder disease, the analysis of the outbreak and development of diseases and the relationship between disease and factors, the logic process of the early warning for flounder disease was confirmed. It consists of five parts: specifying the target, searching for the source, distinguishing the sign, predicting the degree and eliminating the menace. Using the expert survey method the early warning indexes which affect the normal life of the flounder and calculated the range of the water environment factors were also confirmed. Finally, an early warning system was implemented, which can reduce the damage from the flounder disease.

A Call Center Oriented Consultant System for Fish Disease Diagnosis in China

Fish expert systems have been developed to solve the fish disease diagnosis problems. However, despite these inherent advantages, there are some limitations yet in the application of the systems because of the poor infrastructure and low capacity for the use of computers. A Call Center-based consultant system for fish disease diagnosis has been developed to overcome the difficulties, and the objective of this system is the automation of fish diagnostic process based on call center via the telephone. This paper explains the needs for the consultant system, the fish disease diagnosis process and the development of the system. The system structure and its components are described. It can provide the accurate and timely diagnosis, prevention and treatment all around the clock and everywhere the fish sites are located. The experience and the further development of the system are also discussed in the paper. Call Center, fish disease diagnosis, consultant system, knowledge acquisition

A CBR System for Fish Disease Diagnosis

Fish disease diagnosis is a complicated process and requires high level of expertise. However, there’s no accepted general knowledge in fish disease diagnosis. This paper describes a CBR (case-based reasoning) system for fish disease diagnosis. A two-step case retrieve model is proposed in this paper. case-based reasoning, fish disease diagnosis, nearest neighbor

A Web Based Expert System for Milch Cow Disease Diagnosis System in China

A web-based multi-models expert system called DCDDS is presented in this paper, which developed for diagnosis of dairy cow diseases through the symptoms submitted by users on web. As it is accepted that the inference engine and the relevant knowledge representation are the crucial part of diagnosis expert system, which limits its application and popularization in animal disease diagnosis. To break the limit and raise accuracy, this paper compares and appraises the existed systems and presents a solution that contains three models—Case-based reasoning (CBR), Subjective Bayesian theory and D-S evidential theory. Accordingly a knowledge representation method which can support the three different models is also designed. Up to the complicacy of the group of symptoms users acquired, they can choose which of the three models should be adopted to meet the best resolve. The performance of the proposed system was evaluated by an application to the field of dairy cow disease diagnosis using a real example of dairy cow diseases. The result indicates that the new methods have improved the inference procedures of the expert systems, and have showed that the new architecture has some advantage over the conventional architectures of expert systems on both efficiency and accuracy.

Water Quality Management in Intensive Aquaculture in China

Intensive aquaculture is adopted by more and more fish farms in China. This paper focuses on the typical water monitoring and controlling methods in intensive fish culture in Chinese fish farms. The paper illustrates the main factors in fish culturing and the way to control them: dissolved oxygen (DO), temperature, PH, particulate matter and ammonium.

A Wireless Intelligent Valve Controller for Agriculture Integrated Irrigation System

Based on the problems caused by current automatic irrigation system with a large number of cables, such as installation, maintenance, and difficult expansion, this paper proposed a wireless integrated irrigation control system and developed a wireless intelligent valve controller which can satisfy the requirements for agricultural irrigation in our country. The controller consisted of the control unit, power unit, wireless communication unit, relay boost driver unit, state feedback switch, etc. It received the control command from the remote control center by the wireless communication unit, actuated the relay boost driver unit to turn on/off irrigation solenoid valves. The controller includes the functions of remote control, parameter setting, feedback status detecting, etc. Since the rational design, simple command, and low cost, the controllers have been pilot in Beijing and Xinjiang. The results indicate that the controller is effective in practice and can be used a normal irrigation season.

Design of an Intelligent PH Sensor for Aquaculture Industry

Automatic monitoring and controlling system is essential for improvement of aquaculture industry. This paper presents an intelligent PH sensor that applied to water quality monitoring. It involved signal processing, self-calibration. Using low power and high performance microcontroller MSP430F149, Smart Transducer Interface Module (STIM) based on IEEE1451standard was embedded. The design of software and hardware was described in detail, and an initial calibration experiment was carried out to establish a calibration parameter. The results indicate that the pH sensor is more accurate, reliable and easy to use, which is suitable to spread the application in aquaculture industry.

Towards Developing an Early Warning System for Cucumber Diseases for Greenhouse in China

The integrated management of cucumber (Cucumis sativus L.) diseases play a key role in guaranteeing the high quality and security of cucumber production in greenhouse, moreover, the early warning of cucumber diseases is the chief precondition for IPM (Integrated Pest Management). This paper describes an attempt to develop an early warning system for cucumber diseases in greenhouse. By analysing plant disease epidemiology and early warning theory, the conceptual model of early warning on cucumber disease of greenhouse is developed. The data collection, data transfer system, database system, forecast system, warning system, and so on are integrated and an early warning system for cucumber diseases in greenhouse has been designed.

An Efficient Iterative Thresholding Algorithms for Color Images of Cotton Foreign Fibers

The goal of color image segmentation is to divide the image into homogeneous regions. Thresholding is a commonly used technique for image segmentation. Thresholding assumes that image present a number of components, each of a nearly homogeneous value, and that one can separate the components by a proper choice of intensity threshold. In this paper, we present an efficient iterative algorithm for finding optimal thresholds. In the first step, color images were captured, and the edge of color images were detected by edge detection method. In the second step, color images were converted into a gradient map, and then the regular of experience values were analyzed, at last the best threshold of the gradient map was chosen by selecting the best experience value iteratively. The experiment results indicate that the best threshold selection of the gradient map can precisely segment the high-resolution color images of cotton foreign fibers.