This system was created to monitor weather conditions such as temperature, humidity, light intensity, rainfall, pressure, CO
2 level, wind speed and direction in a specific region. The designed system is more adaptive and distributive in nature when it comes to analyzing environmental parameters. This system was had three main units, which were power unit, sensing unit and output unit.
This system was used a 10W solar panel. In high irradiation, it caught 21.2V. This captured 21.2V was transferred to the system’s solar charge control device. 21.2V was converted to 14V in the solar charge controller. That 14V was used to charge a 12V rechargeable battery and divided that 12V into 5V using a voltage regulator. Fig 3 shows diagram of power unit. That 5V was supplied to Arduino Uno microcontroller, all the sensors except BMP180, LCD and GSM-900A. The key component of this system was the Arduino Uno microcontroller. To run it, 5V was provided to the Arduino microcontroller and all other sensors were attached to the Arduino microcontroller. The program was written in Arduino software and uploaded to the Arduino Uno. Temperature and humidity were measured using a DHT11 sensor.
Via voltage regulator, 5V was supplied to the DHT11 sensor.
BMP 180 sensor was used to detect pressure in the atmosphere and supplied 3.3V through Arduino because the operating voltage of the BMP 180 sensor is 3.3V. The FC37 sensor was used to detect rain. There were used three conditions for rain sensors in the programme. Requirements were titled “RAIN,” “RAIN WARNING” and “NOT RAIN.” Rain sensor was sensed rainy data based on values written on coding. In that range, the sensor was detected 0 value, it was displayed “Raining,” the sensor was detected value 1, it was displayed “Rain Warning,” the sensor was detected value 3, it was displayed “Not Rain.” A light sensor was used to detect the brightness of the light. It had a light dependent resistor. That LDR was sensed the brightness of the light. As a working voltage, 5V was supplied through a voltage regulator. The LDR sensor program was provided five conditions: “VERY BRIGHT,” “BRIGHT,” “LIGHT,” “DIM,” and “DARK.” Then five analog values were given for those conditions and the LDR sensor output was based on those analog values. MG811 CO
2 sensor was used to detect CO2 amount in the atmosphere and supplied 5V to the sensor via voltage regulator to operate the sensor. Real time clock sensor was used to provide real time weather data. For this, 5V was supplied through a voltage regulator.
Anemometer was used to detect wind speed. In this system, a cup anemometer was used with a hall effect sensor to detect wind speed. Three cups were used in an anemometer and, based on the rotation of that cups and converted into km/h and used to detect wind speed. Wind vane was used to detect wind direction. 8 IR sensors wereused to detect eight directions in the Wind vane. Both these anemometer and wind direction are very low cost because cheaper materials were used to develop that device. All these sensors were operated according to the programme written on Arduino IDE.
The out-put unit was had I2C liquid crystal display and GSM-900A. Fig 4 shows output unit of the system. LCD was used to display weather data in the field. 16×2 LCD was used in this system but it was difficult to connect 16 pins to the Arduino board. So I2C module was used to reduce 16 pins into 4 pins. It was fixed near to the weather station and anyone who came to the field can easily show the weather situation in the field. GSM was used to send weather data to user in this system. GSM (Global System for Mobile Communications) is a wireless cellular infrastructure that is open and used to transmit mobile voice and data services. In this system, GSM 900A was used because it consumes low power. The standard mobitel sim card was inserted into GSM and 5V was via voltage regulator and connected to Arduino board. If the user needs to know weather data infield, can get weather data without coming to the field. Anywhere, anytime can get weather data to mobile phone through GSM. When the user sends message as “STATE”, user receives weather alert. All these sensors, microcontroller, LCD and GSM placed in louvered type Stevenson screen.
Finally, this system was implemented in the “Smart Agro Tech Park” module. Fig 5 shows smart weather monitoring system. It was sensed all of the accurate weather data in the area, such as temperature, humidity, pressure, light intensity, rain, CO
2 level, wind speed and direction and the data was displayed on the LCD and sent it to the mobile phone.
Using real-time data on weather conditions related to the current location and season assists farmers in taking care of soil and crops as well as managing any weather-related hazards. The applications of IoT in agriculture are domain. IoT sensor based weather monitoring system is one of the main application used to monitor weather automatically. IoT sensors set the groundwork for a larger linked system for agricultural weather monitoring. These systems are based on a network of linked sensors that collect data in the field. The acquired data is then processed by cloud computing systems, which provide warnings and messages about potential weather dangers impacting crops. Farmers can use IoT systems to gain real-time access to environmental and soil data, allowing them to plan actions ahead of weather changes. Advantages of using IoT based weather monitoring system in agriculture are reduce crop hazards by keeping an eye on severe weather patterns, assist farmers in optimizing resource usage and crop protection, improve product quality by advising on the optimal time to harvest, send real-time alerts to many devices and platforms and collect accurate data in the field that is relevant to the location of the farm and the current season.
Sharma, 2019 created an automatic weather station that is operated by electricity. Using electricity is not cost-effective and farmers would pay a premium for it. Today, electricity is the world’s most limited resource. A wide range of industries is now using renewable energy sources. So in this system used solar power to supply power to the system. It is both an energy-saving and cost-effective system. CO
2 is essential for photosynthesis and evidence suggests that increasing CO
2 concentrations will accelerate plant growth. So knowing CO
2 level for farmers is very important.
Veeramanikandasamy et al., 2020 used MQ 135 gas sensor to detect gases. The MQ135 gas sensor detects oxygen, alcohol, ammonia, nitrogen, sulfide, aromatic compounds and smoke. It not exactly senses only CO
2. In this system, used the MG 811 CO
2 sensor which sensed the exact amount of CO
2 level in the atmosphere. Fig 6 shows MG 811 CO
2 gas sensor. MG 811 sensor is better than MQ 135 sensor because farmer can accurately get CO
2 level.
Satyanarayana et al., (2016) used an automatic tipping bucket rain gauge in their weather station to detect rain.
Rahut et al., (2018) created another smart weather station and they used an ultrasonic sensor to detect rainfall levels. In this system was used raindrop sensor. More maintenance need for the automatic tipping bucket rain gauge so difficult to use for farmers. But the raindrop sensor only needs to be installed in the proper place and no need for any maintenance. The automatic tipping bucket rain gauge needs more space to compare to the raindrop sensor. Raindrop sensors only monitor whether it is raining or not and do not provide a rainfall rate. If farmers need to know the rainfall rate they can use the ultrasonic sensor with the raindrop sensor to detect the rainfall rate. So using a raindrop sensor to detect rain is cost-effective for farmers.
Aroos et al., (2011) develop an automated weather station for measuring ground-level weather measurements. In that system, they used a data storage module. Micro SD card used as data storage module and it saved real-time weather data. But in my system, data storage is not available. The data logger is important because for analysis purposes can get previous data.
Munandar et al., (2017) developed a real-time automated weather station. They used a user-friendly interface. The color of the graph varies depending on the weather parameter to improve the accessibility of the user interface. This makes it easy to differentiate between parameters. Temperature increases, temperature changes, atmospheric pressure changes, precipitation changes and solar radiation changes are all represented by the colors red, cyan, purple, blue and pink.
Chawla et al., (2015) used the android interface to showcase the weather data. The key benefit of using this application is that it has a user-friendly interface that eliminates all ambiguity for the user. The interface is divided into several panes for configuring the system and displaying the incoming data. On the terminal pane, the data to be sent or displayed is illuminated. Other panes, such as the toolbar pane, have their own basic application, such as the special characters’ button. These user-friendly interfaces help in clearly displaying weather data to users. However, in this system, weather data is sent to the user’s mobile phone as a message.
The direction of the wind is stated by the direction from which it originated. A north or northerly wind, for example, blows from north to south. Wind direction is typically provided in cardinal (or compass) directions or degrees. As a result, a wind coming from the north has a wind direction of 0° (360°); a wind blowing from the east has a wind direction of 90° and so on. Wind direction measure using wind vane and there is available automatic wind vane.
Kong, (2017) include market available automated wind vane for his smart weather station. The Wind vane has eight switches, each of which is attached to a separate resistor. The WeatherRack calculates the resistor’s resistance value by calculating the voltage around a resistor divider (with 10K Ohm onboard resistor). Normally, the Wind Vane can only sense 8 directions. It is possible to read 16 directions on occasion (when two connections are closed at the same time), although this is an uncommon occurrence. This study created a low-cost wind vane and used 8 infrared sensors. Fig 7 shows wind vane of this system. The wind vane used by Kong in 2017 is very pricey and needs a higher voltage to operate. However, the wind vane that used in this system is inexpensive and uses low power to operate.
Chawla et al., (2015) created an automatic weather station with a HC-05 Bluetooth module to send weather data.
Hussein et al., (2020) developed another automated weather station. The weather station system created using Arduino Uno and ZigBee technologies in combination with sensors. ZigBee technology used to transmit weather data to the end-user.
Srivastava et al., (2020) developed one automated weather monitoring system. In that system used ESP8267 Wi-Fi module to transfer weather data. Wi-Fi, Bluetooth and ZigBee wireless technologies have very short transmitting ranges. But in this system used GSM to send weather datato the end-user. The transmission range of ZigBee is 10-100 m and the Bluetooth module is 10 m meanwhile the transmitting range of a Wi-Fi module is up to 1 km. GSM has a transmission distance of 35 km. From Wi-Fi, Bluetooth module, ZigBee and GSM, GSM has the longest range, making it suitable for outdoor use. Wi-Fi, bluetooth modules and ZigBee are more suited for indoor use. Otherwise, there could be problems with data transmission limitations.