Design Project (BSCpE)--Cavite State University-CCAT Campus, 2017.

Includes bibliographical references and appendices.

BAGORIO, CHERRIE LEI P., and DEL ROSARIO, MEDELYN V. Development of Microcontroller Based Automatic Solid Waste Segregator with GSM Alert System. Project Design. Bachelor of Science in Computer Engineering. Cavite State University - Rosario Campus, Rosario, Cavite. April 2017. Adviser: Mrs Diane P. Arayata. Technical critic: Ariesthotle D. Arive.

The study, to develop the “Microcontroller Based Automatic Solid Waste Segregator with GSM Alert System” started in January 2017 to March 2017 in Cavite State University - Rosario, Campus. Specifically, the study aimed to: design a microcontroller-based automatic solid waste segregator with GSM alert system; construct the system as designed; evaluate the system’s performance in segregating biodegradable and non-biodegradable wastes in terms of the following: time of segregation; response time in sensing waste and pushing it to designated bin; time of texting after the bin reached 80%; time to finish segregating different kinds of wastes; can; plastic bottle; random wastes; accuracy of segregation; and implement in the TVEP Building of Cavite State University Rosario.

Based on the Performance Evaluation, the metal waste took less time to sense and push to designated bin as it is located near the funnel. The plastic/paper waste and biodegradable waste took more time as they were placed in the middle and end of the conveyor respectively. Keyence proximity sensor attached to bin | responded slowly in texting the administrator whenever the bin reaches 80% of its capacity. Compact proximity sensor attached to bin 2 and bin 3 responded faster to notify the administrator. Signal is one problem of GSM module since it has relatively low baud rate compared to cellular phone signal. The time it took to finish segregating 250 grams consisting of 16 cans has an average of 78.61 seconds. Trials 1 and 3 showed that the time stopped because the can clogged inside the funnel and no longer dropped inside the conveyor. The second trial segregated all the wastes dropped and no clogging occurred. The 500 grams consisted of 32 cans has an average of 72.32 seconds, it is faster than 250 grams because of clogging problem and wastes no longer dropped in the conveyor to be segregated. The time it took to finish segregating 250 grams consisting of 11 plastic bottles, has an average of 53.5 seconds.

Clogging is the big problem for all the trials. Half kilo consisting of 21 plastic bottles showed that clogging stopped the operation as wastes no longer dropped in the conveyor. The time showed were when the plastic bottles stuck in the funnel and no longer dropped to the conveyor. The time it took to segregate random wastes of 250 grams consisting of 6 plastic bottles, 6 cans and 6 crumpled papers showed that for trial I, it detected 1 can, 2 plastic bottles and 4 crumpled papers and segregated it to designated bin. Trial 2 detected 3 cans, 1 plastic bottle and 3 crumpled paper. Trial 3 detected a can, 2 plastic bottles and a crumpled paper. Twelve (12) cans, 12 plastic bottles, and 12 crumpled papers consisted the 500 grams. Trial 1 was able to segregate 4 cans and the rest clogged in the funnel and conveyor. For trial 2 and 3, the wastes clogged in the funnel and conveyor.

The accuracy of segregation showed that wastes were segregated and put to proper bin. It showed that sensors function based on its intended use. Cans were sorted properly and push to bin 1, crumpled paper, paper cup and plastic bottles were in bin 2, and the rest which were biodegradable went to bin 3.