Fig 8 show all the components of hardware of this ecosystem Free Essay Example

Fig. 8 show all the components of hardware of this ecosystem consisting of sensors and actuators to control the artificial environment. Every the input sensors provide the environment information in the form of analog voltage ranging from 1-1024 (10bit) and one-wire data (for DHT11). These data are then processed and converted to a readable percentage or rounded figures which can easily be calculated or used as a reference for easier decision making. These are directly connected to the Arduino Mega via its analog pin.

It has a programmable microcontroller that is programmed to get the analog date from the particular analog pin and convert it to digital data. It then appends all the sensor data in digital format and sends it to cloud (in JSON format) per second. The cloud contains a data set containing the optimal values for each environment parameter for the specific crop. The necessary decision is made on the cloud side depending upon the (optimal) threshold and necessary steps for control are sent through the Arduino for modifying the parameters.

The respective environment conditions are sent to Android UI as notifications. The App also consist of control that which we can switch the actuators on or off manually. Arduino Mega (IoT Gateway) also communicates with the actuators through a relay (except the artificial lighting module). The relay is used because we cannot we a direct connection between the control circuit operating at 5V and the output device operating at 12V. The black and the red arrows represent the supply of 5V and 12V power respectively.

The control circuit sends a switching signal to the relay which then provides 12V power supply to turn on the specific actuator. It is shown in Fig. 9 the two-way data transfer from hardware components to cloud and the UI, the data is encoded in JSON format as that’s the default input/output type of the HPE UIOT Platform.

The entire system resides on the fact we have the correct environment parameters values is available for every crop that is to be cultivated. It can be downloaded from any government agricultural site. The dataset is loaded in the cloud, which forms the optimal threshold value for every crop. The various sensor data are then compared to the optimal value to make the decision.

The system constitutes of Arduino Mega microcontroller board, sensors like DHT11 temperature & humidity sensor, a moisture sensor, LDR Sensor, pH Sensor, CO2 Sensor, a Wi-Fi module i.e. ESP8266. The UI software consists of an android application which includes setting up of the profile for predefined crop based on the seasons or on daily and weekly mode. The application has two state auto and manual mode to regulate the actuators. The software has been programmed to send a notification to the farmer whenever the physical parameters sensed are below the threshold value and based on the farmers input a control signal will be sent to the Arduino Mega to either switch ON or OFF the irrigation. The Arduino Mega board controls all the activities taking place on board and acts as the IoT gateway.

The sensor senses all the physical parameters and transmits the data to the gateway. It converts the value to digital percentage form, and then transmits the data to the cloud using the ESP8266 Wi-Fi module. The cloud in our system will include the HPE UIOT Platform, which holds the database and the decision logic. The database will maintain the data received from the sensors. The decision logic then decides whether the farmer action is needed to regulate the climate. For example, in the developed system a threshold value for temperature is kept at 25 ?C. Whenever the temperature goes above the threshold temperature, the database will trigger action to the decision logic. It notifies the farmer through the Smart Greenhouse Android application about the environment condition and the actuator state. The action from app is send to the cloud. It then turns on the Peltier module to heating effect by rotating the servo motor sending a Python shell script.