Internet Of Things (Iot) In Smart Recycle Bin Application Using AI Technology - Liong, Woei Chi (2023)
With the economic growth and rapid industrial development, the amount of solid waste generated has been increases significantly. According to Malaysian Investment Development Authority (MIDA), even though with the increasing of recycling rate of 17.5 percent in 2018, the quantity of solid waste generated rose to 38,000 tons per day. In addition, as refer to the World Wildlife Fund (WWF) Malaysia the quantity of plastic waste generated hold the second highest share among all solid waste generated in Malaysia. Nevertheless, the plastic recycling rate among Malaysian is only 20 percent based on interview made by WWF Malaysia. This has caused a major impact toward the environment. In Malaysia there are 20 public universities and 467 private universities. Not only that, in universities the practice of recycle are significantly low as the intention for universities students to practice recycling in their daily life is a pain for them. In this project, Smart Recycle Bin Application Using Artificial Intelligence (AI) Technology is developed. The web application is also developed to monitor the smart recycle bin status. By using this system, the is a camera that attached to the devices and the AI technology is used to identify recycle item such as paper, plastic, metal, and others. Other than that, the ultrasonic sensor is used to check the status of filling level in the recycle bin and if the recycle bin is almost full, the alert message will be send to top management in web application. By using this system at university, the university’s students able to practice recycling daily. This will improve the university environment and also enhance the awareness of green environment in youngster. Moreover, this also help universities student develop their responsibility towards environment. University’s management able to gain profit from this system. University’s management able to contact or collaborate with authority to collect and sell recycle item when the recycle bin is full. This also will help university’s management to easily manage environment cleanness. Other than that, this system also helps university’s management to reduce human labour cost in maintaining university’s environment. The methodology of developed this system involved in both software part and hardware part. In hardware part, this system used raspberry pi model 4B, ultrasonic sensor, servo motor, web camera and DC motor. The construction of the system used a conveyer belt as the main part which control by a DC motor. The web camera, servo motor will be attached on the side of the conveyer belt. Moreover, the ultrasonic sensor attached in between the conveyer belt and the compartment of the smart bin. The raspberry pi will control all the sensor motion, alert notification of the recycle bin and data transfer to database. In sensor part, The web camera is for the purpose of AI object detection which used the Tensorflow Keras module. The ultrasonic sensor is for the purpose of detect the remaining bin capacity. The servo motor is act as the pusher on the conveyer belt to allow the waste drop into correct compartment. If the height of the compartment is less than 5 cm, an alert message will be sent to the university’s management through telegram. The alert message will display the location of the smart bin which is full. The database used in this system is MySQL. The data collected in the raspberry pi will passed as an array and sent to the phpMyAdmin which has been host to the AWS. In the AWS the data will be sync to the web application automatically. In software part, this system used web application in Laravel framework to display the output of the system which has been host to AWS. In the web application shows the current capacity of each compartment in the smart recycle bin. Moreover, the web application will auto update and refresh within 10 second’s time. Other than that, the report of the recycle trend also been displayed in the web application.