本节的内容是获取作物的温度(和湿度)。

水、光、二氧化碳是植物生长所依赖的因素，温度适宜。

数字农业相关技术：

• 温度测量；
• 自动浇水(土壤过于干燥时浇水，而不是定期浇水)；
• 使用机器人/无人机检查害虫用农药；

温度控制与人工照明、肥料和 CO₂ 水平控制的结合可以实现全年的种植。

本节通过测量空气温度来计算植物的生长和成熟率。

传统的温度控制方法:暖房(人工加热)和温室(阳光)。

例如，种植西红柿的商业温室白天可以将温度设置为25°C晚上设20°C，这样才能获得最快的成长。

依赖库安装温湿传感器：

pip install counterfit-shims-seeed-python-dht 

该库提供的DHT传感器的值可读取温度和湿度。

CounterFit创建界面湿度传感器（humidity sensor）：

1. In the Create sensor box in the Sensors pane, drop down the Sensor type box and select Humidity.
2. Leave the Units set to Percentage
3. Ensure the Pin is set to 5
4. Select the Add button to create the humidity sensor on Pin 5

生长度日，也称为生长度单位（growing degree units），后面简称GDD。这是根据温度衡量植物生长的一种方式。假设一株植物具有足够的水分、养分和二氧化碳，温度将会决定植物的生长率。

每天的 GDD 越多，植物的生长就越快。

公式：

GDD = (Tmax + Tmin) / 2 - Tbase
Tmax: 每日最高温度
Tmin: 每日最低温度
Tbase: 植物的基础温度
单位:摄氏度

比如，玉米大概需要 800 到 2,700 的 GDD 来成熟，基础温度是 10°C。

如果通过使用物联网设备收集温度数据，农民就可以在植物接近成熟时自动收到通知。

源码位于code-publish-temperature\virtual-device\temperature-sensor\app.py

这段逻辑通过mqtt协议每10分钟上传/发布一次当前温度，所以是运行在农田里的IoT设备上。

from counterfit_connection import CounterFitConnection
CounterFitConnection.init('127.0.0.1', 5000)

import time
from counterfit_shims_seeed_python_dht import DHT
import paho.mqtt.client as mqtt
import json

sensor = DHT("11", 5)

id = 'E38E4B36-363E-4CB2-B45B-2F86640BA9CE'

client_telemetry_topic = id + '/telemetry'
client_name = id + 'temperature_sensor_client'

mqtt_client = mqtt.Client(client_name)
mqtt_client.connect('test.mosquitto.org')

mqtt_client.loop_start()

print("MQTT connected!")

while True:
    _, temp = sensor.read()
    telemetry = json.dumps({ 
        'temperature' : temp})

    print("Sending telemetry ", telemetry)

    mqtt_client.publish(client_telemetry_topic, telemetry)

    time.sleep(10 * 60)

源码位于code-server\temperature-sensor-server\app.py

订阅端运行在服务器上，接收来自物联网设备的温度数据，并保存到csv表格里（正常应该是数据库）。如果优化的话，可以在每天晚上计算一下当前积累的GDD，以及还需要的GDD。

import json
import time

import paho.mqtt.client as mqtt

from os import path
import csv
from datetime import datetime

id = 'E38E4B36-363E-4CB2-B45B-2F86640BA9CE'

client_telemetry_topic = id + '/telemetry'
server_command_topic = id + '/commands'
client_name = id + 'temperature_sensor_server'

mqtt_client = mqtt.Client(client_name)
mqtt_client.connect('test.mosquitto.org')

mqtt_client.loop_start()

temperature_file_name = 'temperature.csv'
fieldnames = ['date', 'temperature']

if not path.exists(temperature_file_name):
    with open(temperature_file_name, mode='w') as csv_file:
        writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
        writer.writeheader()

def handle_telemetry(client, userdata, message):
    payload = json.loads(message.payload.decode())
    print("Message received:", payload)

    with open(temperature_file_name, mode='a') as temperature_file:        
        temperature_writer = csv.DictWriter(temperature_file, fieldnames=fieldnames)
        temperature_writer.writerow({ 
        'date' : datetime.now().astimezone().replace(microsecond=0).isoformat(), 'temperature' : payload['temperature']})

mqtt_client.subscribe(client_telemetry_topic)
mqtt_client.on_message = handle_telemetry

while True:
    time.sleep(2)

先运行订阅端，再运行发布端，本地就会生成temperature.csv。

法一，测电阻。电阻传感器有2个探头可以进入土壤。电流被发送到一个探针，并被另一个接收。然后传感器测量土壤的电阻-测量在第二个探头的电流下降多少。水是电的良导体，所以土壤的含水量越高，电阻就越低。

法二，测电容。电容湿度传感器测量可存储在正极和负极电极板上的电荷量/电容。土壤的电容随着湿度的变化而变化，可以转换为可以通过物联网设备测量的电压。土壤越湿润，输出的电压就越低。

Some GPIO pins provide a voltage, usually 3.3V or 5V, some pins are ground, and others can be programmatically set to either send a voltage (output), or receive a voltage (input).

You can use GPIO pins directly with some digital sensors and actuators

像Arduino等设备提供了模拟信号引脚，其实就是内置了ADC。

刚刚说的两种传感器都是模拟传感器，所以可以用这种引脚。

内置集成电路。

I2C, pronounced I-squared-C, is a multi-controller, multi-peripheral protocol, with any connected device able to act as a controller or peripheral communicating over the I2C bus (the name for a communication system that transfers data). Data is sent as addressed packets, with each packet containing the address of the connected device it is intended for.

需要传感器有自己的地址，比如seeed的光感都有一样的地址，按钮也都有一样的地址。

这种方式没怎么看懂。

SPI is designed for communicating over short distances, such as on a microcontroller to talk to a storage device such as flash memory. It is based on a controller/peripheral model with a single controller (usually the processor of the IoT device) interacting with multiple peripherals. The controller controls everything by selecting a peripheral and sending or requesting data.

SPI controllers use 3 wires, along with 1 extra wire per peripheral. Peripherals use 4 wires. These wires are:

On a Raspberry Pi you can use GPIO pins 19, 21, 23, 24 and 26 for SPI.

比如蓝牙、LoRaWAN 、wifi、Zigbee。

One such example is in commercial soil moisture sensors. These will measure soil moisture in a field, then send the data over LoRaWan to a hub device, which will process the data or send it over the Internet. This allows the sensor to be away from the IoT device that manages the data, reducing power consumption and the need for large WiFi networks or long cables.

Zigbee uses WiFi to form mesh networks between devices, where each device connects to as many nearby devices as possible, forming a large number of connections like a spiders web. When one device wants to send a message to the Internet it can send it to the nearest devices, which then forward it on to other nearby devices and so on, until it reaches a coordinator and can be sent to the Internet.

CounterFit传感器和[1.2](# 1.2 CounterFit测温测湿实验)节不一样，这里要用专门的土壤湿度传感器：

1. In the Create sensor box in the Sensors pane, drop down the Sensor type box and select Soil Moisture.
2. Leave the Units set to NoUnits
3. Ensure the Pin is set to 0
4. Select the Add button to create the Soil Moisture sensor on Pin 0

源码位于code\virtual-device\soil-moisture-sensor，可以看出需要用到ADC:

from counterfit_connection import CounterFitConnection
CounterFitConnection.init('127.0.0.1', 5000)

import time
from counterfit_shims_grove.adc import ADC

adc = ADC()

while True:
    soil_moisture = adc.read(0)
    print("Soil moisture:", soil_moisture)

    time.sleep(10)

根据read定义，返回的其实还是百分比：

# input voltage / output voltage (%)
def read(self, channel):
    ''' Read the ratio between channel input voltage and power voltage (most time it's 3.3V). Args: channel (int): 0 - 7, specify the channel to read Returns: (int): the ratio, in 0.1% '''
    return CounterFitConnection.get_sensor_int_value(channel)

传感器是需要校准的。比如lesson 1 的温度传感器就是校准后才输出摄氏度值的。

Sensors rely on measuring electrical properties such as resistance or capacitance.

Soil moisture is measured using gravimetric or volumetric water content.

大概意思就是，中学物理学的，电阻受温度影响，所以有误差。

IoT设备功率很小，扛不住浇水器（water pump）。

继电器，核心是一个电磁铁（electromagnet），将电能转换为机械能。

继电器相当于数字执行器，通电则打开它，断电则关闭它。当然也可以用来切换电路（中学都学过），比如CounterFit里面的继电器就是通过短路来不让电磁铁通电。

添加一个继电器：

1. In the Create actuator box in the Actuators pane, drop down the Actuator type box and select Relay.
2. Set the Pin to 5
3. Select the Add button to create the relay on Pin 5

源码位于code-relay\virtual-device\soil-moisture-sensor

from counterfit_connection import CounterFitConnection
CounterFitConnection.init('127.0.0.1', 5000)

import time
from counterfit_shims_grove.adc import ADC
from counterfit_shims_grove.grove_relay import GroveRelay

adc = ADC()
relay = GroveRelay(5)

while True:
    soil_moisture = adc.read(0)
    print("Soil moisture:", soil_moisture)

    if soil_moisture > 450:
        print("Soil Moisture is too low, turning relay on.")
        relay.on()
    else:
        print("Soil Moisture is ok, turning relay off.")
        relay.off()

    time.sleep(1)

在实际应用中，继电器不应该是由单个土壤湿度传感器控制，而是由一个中心通过多个传感器来判断是否启动。现在引入mqtt协议来实现这一应用。

这次就没有严格的发布端和订阅端了，因为两边都需要订阅和发布topic。

运行在放置了湿度传感器的iot设备上。

源码位于code-mqtt\virtual-device\soil-moisture-sensor

from counterfit_connection import CounterFitConnection
CounterFitConnection.init('127.0.0.1', 5000)

import time
from counterfit_shims_grove.adc import ADC
from counterfit_shims_grove.grove_relay import GroveRelay
import json
import paho.mqtt.client as mqtt

adc = ADC()
relay = GroveRelay(5)

id = 'E38E4B36-363E-4CB2-B45B-2F86640BA9CE'

client_telemetry_topic = id + '/telemetry'
server_command_topic = id + '/commands'
client_name = id + 'soilmoisturesensor_client'

mqtt_client = mqtt.Client(client_name)
mqtt_client.connect('test.mosquitto.org')

mqtt_client.loop_start()

def handle_command(client, userdata, message):
    payload = json.loads(message.payload.decode())
    print("Message received:", payload)

    if payload['relay_on']:
        relay.on()
    else:
        relay.off()

mqtt_client.subscribe(server_command_topic)
mqtt_client.on_message = handle_command

while True:
    soil_moisture = adc.read(0)
    print("Soil moisture:", soil_moisture)

    mqtt_client.publish(client_telemetry_topic, json.dumps({ 
        'soil_moisture' : soil_moisture}))

    time.sleep(10)

控制中心，可以理解成一个小服务器