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Abu Hassan Abdullah
Design and Development of IoT based Garbage Monitoring and Management System
Fuzzy logic based prediction of micronutrients demand for harumanis mango growth cycles
2021-12-01
,
Wan Mohd Nooriman Wan Yahya
,
Lim R.Y.
,
Rudzuan M.N.
,
Sofi Y.
,
Fauzi M.M.
,
Abu Hassan Abdullah
Daily garbage production causes increasing in garbage management and cleansing cost which required an approach for better monitoring and management system to be applied. Currently, demand of IoT keep increasing as a part of Industrial Revolution 4.0 (IR4.0). Eventually, this IoT based Garbage Monitoring and Management System has been developed. For hygiene, self-opening dustbin lid is applied and IoT technology is used to integrate better garbage monitoring and management into an innovative and effective system. The development of this smart bin uses a pair of infrared sensors and an ultrasonic, push notifications were developed in Blynk application, and user-friendly infographic data is designed on webpage for monitoring and garbage management purposes. The smart dustbin notifies the user when the garbage level exceeds 80%. The dustbin sends a push notification to the user's phone to alert the user to take actions needed before the bin exceed the limit.
2021-12-01
,
Wan Mohd Nooriman Wan Yahya
,
Abu Hassan Abdullah
,
Norasmadi Abdul Rahim
,
Erdy Sulino Mohd Muslim Tan
Harumanis is a famous green eating mango cultivar that has been commercially cultivated in Malaysia's state of Perlis. A variety of nutrients are found in soil, all of which are necessary for plant growth. Micronutrients such as Nitrogen (N), Phosphorus (P), and Potassium (K) are essential for Harumanis mango (Mangifera Indica) to growth. The importance of soil fertility in achieving high plant productivity and quality cannot be overstated. It should be used in a moderate amount and in a balanced manner. Predicting appropriate nutrients and the right timing to satisfy the tree's demands is critical. The aim of this study is to create a fuzzy logic-based system to analyse the results of soil tests for nitrogen (N), phosphorus (P), and potassium (K) in the Harumanis mango orchard. The interpreted data are used to estimate N-P-K nutrient levels and indicate the optimal fertilizer solution and application timing for each Harumanis growth stages. The system utilizes Fuzzy Logic Control (FLC) to predict the nutrients demand for Harumanis mango growth. Results shows the system able to calculate and predict values of required N-P-K fertilizer for optimal growth. Thus, assist farmers in predicting the proper amount of N-P-K to apply to Harumanis mango soil.
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