Device

Main Device

The function of our main device is to monitor some parameters of environment, and serve as the terminal of our whole device system. It can detect the temperature, humidity, rainfall, soil moisture content, light intensity, UV intensity, TVOC and other relative parameter in real time. What’s more, there is a built-in pump inside, so our device can water the plants according to the soil moisture, or release inducers such as DAPG according to plants' status of health.

we utilized used computer case to make the shell of our device so as to make it more beautiful.

Fig.1 A photo of our device

All data will be shown in a built-in screen, and be transformed through long-distance 2.4G data transmission module.the transmission distance can be more than 2.5km, so there will be no problem if there is no network in farmland. Meanwhile, there is another built-in 2.4G module to connect with VOC device. What’s more, our device is also possessed of several extendable electric relays to connect itself to more actuators, so as to achieve more goals.

Fig.2 A photo of some components of our device

The component and cost of our device as shown in Table1.

Table1:The component and cost of our device.

Component	Cost($)
Component	Cost($)
arduino mega 2560	10.8
arduino sensor board	3.1
Temperature and humidity sensor	0.9
Rain sensor	0.5
UV sensor	7.7
Light sensor	0.9
2.4G module	5.4
small 2.4G module	1.8
soil moisture sensor	0.9
TVOC sensor	1.8
buzzer	0.9
LED light	0.5
water pump	1.8
Relay * 3	1.8
LCD screen	3.1
Total cost	42.0

We also construct a webapp. The data we acquired can be uploaded to webapp, so that we can check the paramenter of environment and plants’ condition from mobile device in real time. You can open any browser to view the webapp without downloading any extra application.

Fig.3 A screenshot of our webapp

Slave Device

At the time of tobacco encountering disease or pathogen, it will released a series of Volatile Organic Compound (VOC), which will lead to the change of components of air1,2(参考文献). We did GC-MS anlysis of tobacco infected with pathogen.

GC-MS图

Fig.3

We utilized lots of highly sensitive Complementary Metal Oxide Semiconductor(CMOS) gas detectors to capture the change, and establish the training set in advance, using the machine learning method to analyze the obtained data. In this way, we can judge whether our plants encountered disease according to the information from air components.

The sensitive material of the gas detectors is a highly active metal oxide semiconductor, such as SnO2. Under the working conditions, when the sensor encounters a reducing gas, the oxygen anion on its surface decreases due to the redox reaction with the reducing gas, resulting in a decrease in the resistance of the sensor. The resistance of the sensor is related to the concentration of the gas, and each sensor has a special sensitivity to a certain type or a class of gas. It is important to note that e-nose can’t sense a specific VOC like mass spectrometers did, instead, it catch the overall characteristics of VOC as a “fingerprint”.

Highly sensitive CMOS gas detectors we used are illustrated in Fig.3.

Number	Sensor Type	Performance characteristics	Minimum detection limit of related gas
a	IST-8000	Highly sensitive to all types of VOC	1 ppm
b	TGS2600	Sensitive to cigarette smoke and cooking odors	1 ppm
c	TGS2610	Sensitive to alkanes such as liquid gas propane butane, low sensitivity to alcohol	10 ppm
d	TGS2603	Sensitive to ammonia and sulfide gas	1 ppm
e	MS1100	Highly Sensitive to aldehydes, toluene and organic solvents	1 ppm
f	TGS2611	Sensitive to methane	10 ppm
g	TGS2602	Highly sensitive to all types of VOC	1 ppm
h	MQ-7	Sensitive to carbon monoxide and other gases	10 ppm
i	MQ-135	Sensitive to ammonia,sulfide and benzene vapor, or harmful smokes	10 ppm
j	TGS822	Sensitive to alcohol and organic solvents	50 ppm
k(substitute b later)	iAQ-core	Extremely high sensitivity to all types of VOC and can output the equivalent concentration directly	125 ppb

Table1: Highly sensitive CMOS gas detectors we used(All of these detectors have long-term stability)

Fig.4 仪器外观

We also have constructed the relevant gas path. We utilized the three-way valve and single-chip control to achieve automatic and standardized measurement, so that the data between the groups can be compared. Measured data can be directly transmitted to the computer through the 2.4G data transmission module, or summary to the main device to achieve ultra-long distance transmission. When the slave device is connected to the master device, the main device automatically recognizes the presence of the slave device and does data transformission. The measurement diagram and flow chart are as Fig. shows.

Fig.5 气路示意图 +标准化流程图

There is median filter algorithm in SCM to remove the extremums. We firstly preprocessed the data: identified and removed the base line values, after that, read the response value on 1min, 2 min, and the average value and maximum value of the response curve. Then, we used the machine learning method to analyze the obtained data. Click here to see the details of our modeling process. We achieved more than 90% accuracy rate of sensing the tobaccos’ health condition. Moreover, based on the result of the modeling, four CMOS detectors were enough to make a judgement for tobaccos health condition, which means that we can further reduce the cost of our device.

We have designed the visual interface, on which you can choose different work mode of our device.

Fig.6 操作界面照片

We have constructed a webapp. We plan to add more functions to it in future, for example, we can get to know whether our plants are in good condition directly.

Fig.7 Webapp截图

How to use our device? Let's watch the following video!

However, our device remains some problem unsolved, for example, it is not sensitive when the concentration of gas is too low, and we need to establish the different training set when it is used in different area. Hence, we plan to enhance various functions and capabilities of our device in the future.

Click here to see the details of our improvement.