An Algorithm for an IoT Prawn Feeder in Conjunction with an Aquaponics System

Abstract

Aquaponics has gained recognition through its food sustainability with different combinations of aquaculture and hydronics. Freshwater prawn (Macrobrachium Rosenbergii) can be bought for less than ten cents per prawn and is becoming a popular aquaculture choice for farmers in their aquaponic system. This thesis will demonstrate how developing an algorithm for a freshwater prawn conveyor-based feeder will help farming prawn become a viable option in developing countries and a sustainable food source. Currently, majority of the human population growth is in developing countries where starvation, lack of food sustainability, and lack of resources exists. Here we are today with no devices available specifically for feeding prawn. The current methods are to feed by hand which requires time and effort to measure out the food and dispense it into the habitat. The other choice farmers currently use are deer style feeding system that will either over feed or under feed the prawn which can alter the water characteristics and kill a significant percentage of prawn. We devise an experiment by developing an algorithm with a conveyor feeding system that will dispense food based on the habitat dimensions, maturation of prawns, and the number of prawns. By providing this technology, farmers with any farming background will not have to worry about misfeeding prawn or having to consider all the necessary factors to dispense the correct amount of food. This algorithm has a calibration file that allows it to be used with any conveyor system.