A new environmental monitoring system for silkworm incubators

System monitoring overview

Figure 1 shows the proposed conceptual model of the monitoring system. There are three main stages: the reading of sensors, the communication channel, and storage of data in the cloud. The system is scalable and it is possible to include other sensors and communication technologies. It consists of several sensors that record environmental parameters such as moisture, temperature, and luminosity in a silkworm incubator. The information is then uploaded to the cloud by Google Drive. We used two different sensors to collect data on temperature, humidity, and luminosity. Wi-Fi communication was used to upload the information to Google Drive. Users obtain information about the data recorded with a username and password through a smartphone or any device that supports the Google Drive application.

Figure 1. Silkworm incubator monitoring system conceptual model.

Silkworm incubator

The silkworm incubator structure keeps the environment in uniform conditions for temperature and humidity (see Figure 2 and Figure 3). These are the most important variables to control. The water tank is located at the bottom, with a capacity for eight liters of water. The incubation chamber has nine metal mesh trays to allow air flow. The incubator brand is Incubapremium, manufactured in Colombia by Abraham Reyes Sanclemente incubation equipment specialist with 30 years' experience.

Figure 2. Silkworm incubator, front on view.

Figure 3. Silkworm incubator, inside view.

Silkworms are distributed in trays that are about one meter wide and 60 cm long, which facilitates their handling. The materials used for their construction are aluminum and thermal insulation. The trays are placed to form shelves called swaths. Each tray, of the nine that make up the shelves, is separated by approximately 15 cm. The temperature inside the chamber is controlled by a heating system based on an electrical resistance. The humidity is controlled by a humidifier located at the bottom side of the chamber.

Temperature and humidity regulation

Temperature and humidity plays a vital role in the rearing of the silkworms. As silkworms are cold-blooded animals, the temperature will have a direct effect on various physiological activities¹. Humidity’s role in silkworm rearing is both direct and indirect⁵. The combined effect, of both temperature and humidity, largely determines the satisfactory growth of the silkworms and production of good-quality cocoons. It directly influences the silkworm’s physiological functions. The selected sensor was DHT22, which is an essential temperature and humidity digital low-cost sensing device. This sensor has the capability to obtain new data every 2 seconds.

Luminosity regulation

Silkworms, like other animals, are photosensitive and tend to crawl into dim light. They do not like strong light or complete darkness^1,9–11. The breeding of silkworms in continuous light slows down growth and reduces both the weight of the larvae and the cocoon. We choose the luminosity sensor APDS-9301 due to the high precision in measurement and its low power consumption.

Embedded platform

Raspberry Pi version 3 (RPi3) was chosen for this project, due to its small size and low cost, compared to conventional PC and data loggers, plus zero cost of free Linux software¹¹.

RPi3, in comparison to most of the other Linux-based embedded systems, such as Arduino Due, Beagle Bone Black, and Intel Edison, has a better cost-benefit ratio, broader user community, and a more standard programming language and communication, many input-output pins and a graphics interface¹². A picture of the RPi3 is shown in Figure 4.

Figure 4. Raspberry pi version 3 board used to develop the monitoring system.

Hardware and software development

The prototype hardware consisted of an RPi3 board inside a plastic box, nine sensors to measure temperature and humidity, and one luminosity sensor. The plastic box was used to protect the RPi3. All of the sensors were placed inside of the silkworm incubator. As aforementioned, the silkworm incubator has nine levels. Therefore, one temperature and humidity sensor was placed in each level and the luminosity sensor was placed in the incubator middle. In the initial design of the monitoring system, we considered necessary only a single light sensor due to the uniform light conditions for all levels.

The monitoring system was developed in three phases: the design of monitoring system architecture, hardware and software requirements, and the implementation.

All the hardware documentation such as schematics of circuits, types of sensor and material specifications used are available in GitHub, along with the documentation of the software developed, such as the communication algorithms between sensor and RP3, the storage algorithm, and the communication algorithm between RP3 and Google Drive service. Furthermore, instructions to install the different libraries necessary for the monitoring system are also contained here.

Architecture of the monitoring system. In the architectures of monitoring systems sensors, data gathering can vary, including data transmission (wired or wireless technologies), data storage and usage of intermediate devices. A particular monitoring system can also be supplemented with decision support system, which is responsible for data analysis, incubator environment condition determination and appropriate decision selection.

In our monitoring system, by the usage of RP3 the data from sensors using wired communication is transferred and uploaded to the cloud by Google Drive for further analysis (see Figure 5).

Figure 5. Architecture of the monitoring system.

Hardware and software requirements. The hardware requirements are the materials aforementioned and the various sensors. The RP3 works with an SD card. It should work with any compatible SD card, although there are some guidelines that we followed from the official documentation for the Raspberry Pi, written by the Raspberry Pi Foundation with community.

The software requirements for the monitoring system are the installations of: the operative system for RP3, the library of the temperature and humidity sensors on RP3, the library of the light sensor, and the Google Drive on RP3. Furthermore, it is necessary to choose the programming language to use; we used Python language. However, other programming laugages can also be used, such as Ruby or C/C++. The instructions for installing all the software required are available in the GitHub repository as follows:

The main algorithm of the monitoring system works by initializing the sensors variables to zero; there is a query time where it collects sensor data. The program asks for the time elapsed and if the time elapsed is less to 5 minutes, the system accumulates the sensor values. When the time lapsed exceeds 5 minutes, the program calculates the average of collected sensors values (temperature, humidity, and light) and updates a txt file, which is synchronized with the file on Google Drive. The algorithm for this is available on our GitHub repository.

Field test

For a field test, worms were obtained through resources provided by the National Ph.D. Scholarship for Teachers granted by the Human Talent Training Network Project for Social and Productive Innovation in the Department of Cauca - InnovAcción Cauca. The monitoring system was used in one incubator. The condition environments of 200 worms was monitored for 25 days continuously.