Authors :
Nikhil Pradip Parsawar; E. Pavan Kumar; Jai Lakshmi; Ravi Teja; Deba Chandan Mohanty; Bharani Kumar Depuru
Volume/Issue :
Volume 9 - 2024, Issue 6 - June
Google Scholar :
https://tinyurl.com/2bj82erm
Scribd :
https://tinyurl.com/47xyja7j
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24JUN629
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Detecting and dealing with waste
contamination is a big problem in things like managing
the environment, getting rid of waste, and recycling. Right
now, people have to check waste by hand, which takes a
lot of time and can sometimes make mistakes. Our idea is
to use computers to help with this. We've come up with a
way to quickly and accurately find out if waste is
contaminated or not, which can make managing waste
much better.
Here's how it works: First, we clean up pictures of
waste to make them clearer. Then, we use fancy computer
programs to look at the waste and figure out if there's
anything bad in it. These programs use special learning
techniques to get good at spotting different kinds of
contamination in the waste.
We tested our method to see how well it works. It
turns out that it's pretty good at finding and dealing with
waste contamination, no matter what the environment is
like or what kind of waste we're dealing with.
By using this method, we can save a lot of time and
effort because we don't need people to check waste by
hand anymore. Plus, we can keep an eye on waste in real-
time, so if there's any contamination, we can deal with it
quickly.
In the end, our idea is a big step forward in managing
waste better and protecting the environment.
Keywords :
Waste Management, Biodegradable, Non- Biodegradable, Contamination, YOLO, Detectron, Roboflow
References :
- Yue, X.; Qi, K.; Na, X.; Zhang, Y.; Liu, Y.; Liu, C. Improved YOLOv8-Seg Network for Instance Segmentation of Healthy and Diseased Tomato Plants in the Growth Stage. Agriculture 2023, 13, 1643. https://doi.org/10.3390/agriculture13081643
- Afthab, Mohammed & . C, Sri. (2024). Advancing Object Detection A Comprehensive Study Utilizing Detectron2 Framework.
- Merz, Grant, et al. "Detection, instance segmentation, and classification for astronomical surveys with deep learning (DEEPDISC): DETECTRON2 implementation and demonstration with Hyper Suprime-Cam data." Monthly Notices of the Royal Astronomical Society 526.1 (2023): 1122-1137.
- Abdusalomov, A.B.; Islam, B.M.S.; Nasimov, R.; Mukhiddinov, M.; Whangbo, T.K. An Improved Forest Fire Detection Method Based on the Detectron2 Model and a Deep Learning Approach. Sensors 2023, 23, 1512. https://doi.org/10.3390/s23031512
- Xie, Enze, et al. "SegFormer: Simple and efficient design for semantic segmentation with transformers." Advances in neural information processing systems 34 (2021): 12077-12090.
- S, Mohanapriya & S, Mohana & T, Kumaravel & P, Sumithra. (2023). Image Detection and Segmentation using YOLO v5 for surveillance. Applied and Computational Engineering. 8. 160-165. 10.54254/2755-2721/8/20230109.
- Fang B, Yu J, Chen Z, Osman AI, Farghali M, Ihara I, Hamza EH, Rooney DW, Yap PS. Artificial intelligence for waste management in smart cities: a review. Environ Chem Lett. 2023 May 9:1-31. doi: 10.1007/s10311-023-01604-3. Epub ahead of print. PMID: 37362015; PMCID: PMC10169138.
- Sarker, M.M.K.; Makhlouf, Y.; Craig, S.G.; Humphries, M.P.; Loughrey, M.; James, J.A.; Salto-Tellez, M.; O’Reilly, P.; Maxwell, P. A Means of Assessing Deep Learning-Based Detection of ICOS Protein Expression in Colon Cancer. Cancers 2021, 13, 3825. https://doi.org/10.3390/cancers1315382
Detecting and dealing with waste
contamination is a big problem in things like managing
the environment, getting rid of waste, and recycling. Right
now, people have to check waste by hand, which takes a
lot of time and can sometimes make mistakes. Our idea is
to use computers to help with this. We've come up with a
way to quickly and accurately find out if waste is
contaminated or not, which can make managing waste
much better.
Here's how it works: First, we clean up pictures of
waste to make them clearer. Then, we use fancy computer
programs to look at the waste and figure out if there's
anything bad in it. These programs use special learning
techniques to get good at spotting different kinds of
contamination in the waste.
We tested our method to see how well it works. It
turns out that it's pretty good at finding and dealing with
waste contamination, no matter what the environment is
like or what kind of waste we're dealing with.
By using this method, we can save a lot of time and
effort because we don't need people to check waste by
hand anymore. Plus, we can keep an eye on waste in real-
time, so if there's any contamination, we can deal with it
quickly.
In the end, our idea is a big step forward in managing
waste better and protecting the environment.
Keywords :
Waste Management, Biodegradable, Non- Biodegradable, Contamination, YOLO, Detectron, Roboflow