Project Description :
Nowadays, fish farmers are using the traditional feeding system to feed their fish. This method depends on human labour to do the feeding task. Therefore, it is exposed to the high possibilities of human error. One of the problems caused by this method is the issue of overfeeding and underfeeding of the fish. This problem occurs due to the inconsistency of feeding time and the amount of food pallet given to the fish. Consequently, it causes non-uniform fish, pond pollution and in some cases can cause nutrition deprivation. Realizing this problem, this project proposes an Intelligent Fish Automation Feeder. It hybridizes the fuzzy logic and expert system technique to solve the fish feeding problem. This prototype targeted to assist the fish farmer to feed their fish with the right amount of pallet required for that particular fish species with the right type of pallet given at a right time. This prototype requires the input of fish species, the feeding schedule (morning, noon, evening), the amount of fish, the fish’s size (inch), the days of cultures (days) and the water temperature (Celsius) from the user as input. Then, it generates the amount of pallet, the feeding time and the type of pallet. The feeder receives the amount generated from the system and start to feed the fish. The right amount of pallet, time and the pallet type is vital to ensure that the fish farmer gets a good production of their fish. The knowledge in the form of rules has been validated with the experts in this field.
Research/Project Team :
- Nurzeatul Hamimah Abdul Hamid ( Project Leader )
- Mohammad Amirul Asyraf
- Mohd Razif Shamsuddin
Contact Person :
Nurzeatul Hamimah Abdul Hamid ( nurzeatul@tmsk.uitm,edu.my )