DEVELOPMENT OF AUTOMATED PH CONTROLLER SYSTEM FOR NFT HYDROPONIC

In a hydroponics system, pH level is one of the most important parameters that affect the way plants respond to a hydroponic nutrient solution. The range of pH levels depends on the type of plants in the hydroponic system. The plant can uptake nutrients efficiently if the nutrient solution needs to be consistently controlled within the pH range. It is important to ensure a balanced pH level in nutrient solutions to maintain the proper growth of plants. Therefore, the pH level in the nutrient solution will automatically be controlled in this Arduino-based system. A mini NFT hydroponic system was used as a project set up to measure the performance of a pH sensor. Utilizing the pH sensor, will measure the pH level of the nutrient solution and send the data to Arduino. Then, the Arduino will receive, process and send the output signal to the peristaltic pump to transfer the pH adjuster solution into the nutrient solution tank until the desired pH level is achieved. The data of the pH, Electrical Conductivity (EC) and temperature of the nutrient solution for the Amaranth plant growing period of 23 days are collected. The result obtained shows that the system is capable of automatically maintaining the pH level in the nutrient solution

Open-cathode hydrogen experimental of 5-watt polymer exchange membrane fuel cell / Mahanijah Md Kamal

In this work, an analysis of an open-cathode hydrogen pressure based on experimental approach was conducted at Alternative Energy Research Centre, Faculty of Mechanical Engineering Universiti Teknologi MARA Shah Alam. The polymer electrolyte membrane (PEM) fuel cell is a custombuilt device consisting of five membranes or cells. The aim is to observe the polarization curve of 5 watt PEM fuel cell. The experiment on the PEM fuel cell has been conducted for data collection and analysis. The performance of fuel cells was measured by varying the hydrogen supply (supplied at the anode side and the relative humidity. The outputs of PEM fuel cell were measured in net power, watt and stak voltage, volt where the curve was plotted. The result obtained from the experiment shows a similarity in the trend of the polarization characteristic curve

Development of smart chicken poultry farm

In Malaysia, most agriculture industries are still using conventional method to operate. All routines in monitoring and control of chicken poultry farm, for example, utilise man power where the source and energy are very limited. However, the demand from consumers towards the agricultural output is increasing day by day and requires more advanced farming technology in order to obtain maximum efficiency. This paper is focused on the development of smart chicken poultry farm to provide monitoring and control of the farm condition. The electronics, embedded systems and wireless technology are integrated with farm monitoring. Using Master-Slave concept, sensors are used to measure the ambient temperature, ammonia and humidity of the hall of chicken poultry for each slave. The sensors’ readings are then transmitted wirelessly over radio frequency by serial communication using HC-12 RF module to master for further data processing. The design process of both master and slave involved the interfacing of microprocessor, ATMEL ATMega328 with several analogue sensors, LCD, buzzer, relay output, monetary push button and light indicator. Based on the readings from the sensors, the microcontroller produced the output which is connected to the fan for better air ventilation in the chicken poultry farm. Furthermore, PID controller has been integrated to optimize the output control method, hence optimizing hall condition which results to better output for the farm. The system has been successfully implemented and tested at Myra Farm & Services, located at Kalumpang, Tanjung Malim, Perak, Malaysia

Classification of leaf disease from image processing technique

Disease in palm oil sector is one of the major concerns because it affects the production and economy losses to Malaysia. Diseases appear as spots on the leaf and if not treated on time, cause the growth of the palm oil tree. This work presents the use of digital image processing technique for classification oil palm leaf disease sympthoms. Chimaera and Anthracnose is the most common symtoms infected the oil palm leaf in nursery stage. Here, support vector machine (SVM) acts as a classifier where there are four stages involved. The stages are image acquisition, image enhancement, clustering and classification. The classification shows that SVM achieves accuracy of 97% for Chimaera and 95% for Anthracnose

Development of Smart Chicken Poultry Farm

In Malaysia, most agriculture industries are still using conventional method to operate. All routines in monitoring and control of chicken poultry farm, for example, utilise man power where the source and energy are very limited. However, the demand from consumers towards the agricultural output is increasing day by day and requires more advanced farming technology in order to obtain maximum efficiency. This paper is focused on the development of smart chicken poultry farm to provide monitoring and control of the farm condition. The electronics, embedded systems and wireless technology are integrated with farm monitoring. Using Master-Slave concept, sensors are used to measure the ambient temperature, ammonia and humidity of the hall of chicken poultry for each slave. The sensors’ readings are then transmitted wirelessly over radio frequency by serial communication using HC-12 RF module to master for further data processing. The design process of both master and slave involved the interfacing of microprocessor, ATMEL ATMega328 with several analogue sensors, LCD, buzzer, relay output, monetary push button and light indicator. Based on the readings from the sensors, the microcontroller produced the output which is connected to the fan for better air ventilation in the chicken poultry farm. Furthermore, PID controller has been integrated to optimize the output control method, hence optimizing hall condition which results to better output for the farm. The system has been successfully implemented and tested at Myra Farm & Services, located at Kalumpang, Tanjung Malim, Perak, Malaysia.In Malaysia, most agriculture industries are still using conventional method to operate. All routines in monitoring and control of chicken poultry farm, for example, utilise man power where the source and energy are very limited. However, the demand from consumers towards the agricultural output is increasing day by day and requires more advanced farming technology in order to obtain maximum efficiency. This paper is focused on the development of smart chicken poultry farm to provide monitoring and control of the farm condition. The electronics, embedded systems and wireless technology are integrated with farm monitoring. Using Master-Slave concept, sensors are used to measure the ambient temperature, ammonia and humidity of the hall of chicken poultry for each slave. The sensors’ readings are then transmitted wirelessly over radio frequency by serial communication using HC-12 RF module to master for further data processing. The design process of both master and slave involved the interfacing of microprocessor, ATMEL ATMega328 with several analogue sensors, LCD, buzzer, relay output, monetary push button and light indicator. Based on the readings from the sensors, the microcontroller produced the output which is connected to the fan for better air ventilation in the chicken poultry farm. Furthermore, PID controller has been integrated to optimize the output control method, hence optimizing hall condition which results to better output for the farm. The system has been successfully implemented and tested at Myra Farm & Services, located at Kalumpang, Tanjung Malim, Perak, Malaysia