Virtual Booth

BACKGROUND:

The world produces approximately 2.24 billion tons of municipal solid waste annually, with at least 33% not properly managed.  About 50% of household waste consists of recyclable materials like paper, biodegradable waste, and metals. While recycling is essential for sustainability, waste segregation is the foundation that ensures recycling efforts are effective. Without proper segregation, recyclables can become contaminated, making them unusable and reducing the efficiency of recycling facilities.

OBJECTIVE:

1.       To create a segregation system using the electrostatic field and electromagnetic field in one machine

2.       Automation of the distribution of waste to three segregation compartment using AI (artificial intelligence) via Arduino coding.

3.       Using solar energy to provide the electricity power supply

4.       To investigate efficiency of EMES segregation system versus manual segregation

5.       To investigate the quality of segregation in EMES segregation system

METHODOLOGY:

The electrostatic field (ESF) is generated using the principle of the Van-de-Graaff-Generator while electromagnetic field (EMF) is generated using an electric current running through a copper wire coil around an iron rod. The ESF field is to segregate non-metal waste such as hair and plastic while the EMF field is to segregate the metal waste. After the initial two segregation processes by the EMS and EMF, the rest of the waste (such as paper) is channeled to the third compartment, known as the paper compartment. Artificial intelligence (AI) is used for automation. First automation is meant for the detection of a human approach by its ultrasonic sensor and to open its cover for accepting waste. At the same time, it also initiates the electricity power for the generators for the electrostatic field and electromagnet field. Second automation is meant for the detection of waste in its collector using its ultrasonic sensor and activates 3 motors in sequence.  The first motor is to pull the collector into the electrostatic field, and a delay of 20 seconds is programmed to allow the electrostatic field to segregate the waste material. After 20 seconds, the second motor is activated and pulls the collector to the side of the electromagnetic field. Again, a 20 second is programmed to allow the electromagnetic field to segregate the metal material. After that, the third motor is activated to tilt the collector backward to drop the rest of the waste into the third compartment.

Data were collected for analysis to compare the time it takes to segregate recyclable from non-recyclable waste materials between EMES and manual segregation methods. Comparisons were also made on the quality of waste segregation.

RESULTS:

EMES segregation system has a fixed time of 80s for segregation the recycled waste materials (metal and non-metal) from the non-recycled waste materials (human hairs) in all 10 trials.  EMES is 100 % consistent (no variability). In Manual Segregation, time varies across trials (ranging from 250 to 600 seconds). Manual has high variability (SD ≈ 117.6) and is slower on average (4.4x longer than EMES). EMES is significantly faster with p < 0.001 (Mann-Whitney U test). Manual segregation of similar waste materials conducted for 10 samples took a mean time of 361.8s (p < 0.001).

The quality of segregation material was significantly better for metal recycling materials by electromagnetic field as compared to non-metal segregation using electrostatic field (Fisher’s Exact test, p <0.05).  The electromagnetic field has lower contamination (20% vs. 50%). Electrostatic Field is 2.5x more likely to have contamination. In Point-Biserial Correlation analysis, for Electrostatic Field (the only variable group with time variability), correlation is weak for the electrostatic field between contamination rate and time spent (r ≈ 0.1, p > 0.05).  Contamination is not directly explained by time spent in electrostatic segregation. When compared to electrostatic field segregation, the electromagnetic field segregation was 11x more efficient.

CONCLUSION:

The EMES segregation system is faster and more efficient than manual segregation, while Electromagnetic Field produces high quality segregation.