LITTER SCAN: An AI Powered Litter Detection System

Litter Scan: an ai powered litter detection system

~The Ultimate AI Tool To Detect & Combat Litter Pollution Like Never Before!

LitterScan is BuildFuture AI’s cutting-edge, wholesome AI solution, marking an innovative step towards a cleaner and greener future. With automation, real-time analytics, and scalability, it promotes intelligent ways to conquer the problem of litter detection.

About the client

In the global fight against environmental pollution, a US-based client approached us with a wish to launch their own AI solution for litter detection. They wanted us to develop cutting-edge technology that could be integrated into various cameras and systems and help private organizations or municipal corporations detect litter from the far end. This technology was not only to spot litter of different types in varying weather conditions but also to enable proactive measures in maintaining cleaner public spaces.

did you know?

A National Litter Study by Keep America Beautiful 2020 claimed that there are around

Problem STatement

Our client was determined to work for the environment’s betterment, and they witnessed some major problems in the conventional ways of pollution monitoring, for which they decided to introduce an advanced tech solution.

Inefficient Manual Monitoring: The process of keeping a check on litter and the offenders manually was quite time-consuming and ineffective in covering larger areas.

Resource Allocation: Limited resources made it challenging to monitor and manage the litter across large spaces effectively.

Environmental Hazards: Littering not only exploits the surrounding’s aesthetic appeal but also results in environmental hazards affecting wildlife and ecosystems.

We were delighted to have heard our client’s perspective, and we at Build Future AI have always looked out for ways to sustainable development and environment enhancement. This shared vision drove us to enthusiastically proceed with the project and join hands with our thoughtful client.

our solution

LitterScan: Way Forward To A Cleaner & Greener Future

Our proficient R&D team collaborated with the client to properly understand their wants and needs, and our expert developers built an innovative AI solution that makes litter detection as easy as a walk in the park

our approach

Research: Extensive research was conducted to design and develop the LitterScan technology, including conceptualizing algorithms, prototyping, and feasibility testing.
Data Collection and Preprocessing: Diverse data images of different types of litter ((plastic bottles, cans, paper, etc.) in various environments (parks, streets, beaches, etc.), occlusion, and lightning, using datasets like PlastOPol and TACO were gathered and prepared
AI Model Training: Suitable deep learning approaches like Faster R-CNN, Mask R-CNN, YOLO, etc., for various object detection tasks, were selected, the model was trained using various techniques and parameters, and the training process was monitored by tracking metrics.
Integration: Integration of LitterScan with the client's existing systems and workflows, ensuring seamless operation and data synchronization.
Evaluation and Optimization: Rigorous testing and optimization phases to check and improve the system’s performance and reduce false positives/ negatives.
Deployment: The AI model was then deployed to the solution for live monitoring and management and again tested with real-time data.
Continuous Monitoring and Improvement: : The model’s performance in the real-world scenarios was continuously monitored, and feedbacks were considered using which it was fine-tuned.

LitterScan’s Framework

The framework we designed included mobile edge computing, big data analysis, machine learning, and artificial intelligence. The architecture comprises three distinct layers: Sensor Layer, Processing Layer, and User Interface Layer. First, the Sensor Layer captures images of the street on a moving device and pre-processes the collected data. Additionally, the moving device records the geographical location to let the end users track litter easily. Second, the Processing Layer collects all the pre-processed images with their location to perform additional processing on the incoming images, which are then run through DL algorithms for object detection and classification. Last, the User Interface Layer stores the results, including pictures, type, and location of the litter for visualization and reporting.

This three-layer architecture efficiently integrates data acquisition, processing, and user interaction, enabling a comprehensive, smart, clean street service system.

Results

Enhanced Efficiency

LitterScan drastically enhanced the efficiency of litter detection and reduced the need for manual intervention and time required for monitoring.

Improved Environmental Health

LitterScan’s instant litter detection contributed to cleaner public spaces, reducing environmental pollution and promoting public health.

Resource Optimization

By automating the litter detection tasks, LitterScan solved the budget problem, enabling the money to be used on more critical tasks for the welfare of society.

Community Engagement

By micro-managing the littering offenders and by offering transparency, LitterScan fostered community engagement and encouraged cooperation in maintaining the cleaning and combatting littering.

Cost Savings

LitterScan’s cutting-edge automation helped the company improve its operational efficiency and reduce repetitive cleaning efforts, which would save costs in the long run.

frequently asked questions

Get the answer you need

Litter varies in shapes and sizes, from cigarette butts to tires and plastic bottles, making it hard to develop models that identify and classify all waste types.

To tackle this challenge we trained the LitterScan with high-quality datasets and used sophisticated image processing techniques so that it can handle the variability in litter appearances accurately.

Varying environmental conditions with different types of lightning during the day and night, weather, traffic flow, and vegetation affect the visibility and detection of litter.

AIaaS allows businesses to employ the prominence of AI’s machine learning, deep learning, and advanced API algorithms, making it whole at significantly lower cost. Using AI in business can improve their core functionality, eliminating the need for training and other decision-making areas. AI provides flexibility, ease of use, and scalability to businesses, resulting in cost reduction, speed, simplicity, customization, and efficiency in the overall process.

Immediate litter detection and fine issuance via AI-backed cameras and systems would require a high-speed operation and accuracy that would be capable of analyzing images and videos in real-time.

AIaaS improves business automation with the seamless integration of chatbots and digital assistants that handle numerous queries, making the simplest conversations with customers and answering basic queries from employees. AI helps quick decision-making by analyzing vast amounts of data and converting findings into convenient visual formats. Focusing on the latest trend in AI, it is expected to offer continuous growth, cost-effective results, faster implementation, and lower entry barriers.

Integrating such advanced AI algorithms or systems into the existing administrative and road infrastructure, like surveillance cameras and roadside sensors, raises technical problems related to compatibility, connectivity, and data interoperability.