Table of Contents
Introduction
“Your garbage deserves better and so does the planet.”
In a world where climate change has become a major threat, the need for a solution has never been more important. TrashScan is a new AI-powered recycling company that seeks to transform the recycling process. Using a series of sensors, and LIDAR cameras, the TrashScan artificial intelligence model automatically sorts all types of garbage and waste materials that are inputted. TrashScan is here to revolutionize and improve the recycling industry by lowering carbon emissions, reducing landfills, and saving resources.
An issue with current trash collection systems is their effects on the currently available recycling systems. Once garbage is collected in a landfill, it becomes difficult to process and financially taxing. Only 17.6 percent of waste collected gets recycled, while the remainder is thrown into landfills. This causes the waste to pollute the earth and increase carbon emissions by a staggering 5 percent. Our solution involves sorting the garbage in the first step, right after it is disposed to minimize the strain on current recycling systems and maximize the profits gained from recycling material that using current systems would end up in landfills. Through our integrated wireless network, we can provide our customers with comprehensive data analytics.
TrashScan will help the world deal with waste management by providing a more efficient and accurate service. Current recycling systems are plagued with human error and cross-contamination, issues that TrashScan aspires to resolve. Additionally, current recycling methodologies have allowed rodents to thrive, increasing their population by 50% since 2010. If left untreated, these issues will continue to exacerbate the climate crisis as landfills continue to overfill.
Project Description
While TrashScan offers a promising solution to optimize waste management, current recycling rates reveal significant room for improvement. For instance, despite diverting 1,110.3 tons of MGP daily, the residential recycling rate remains at 17.6%, reflecting a decline from the previous year and lagging behind cities with more advanced waste management systems. This emphasizes the critical need for innovative technologies like TrashScan to contribute to avoiding these challenges and driving progress toward higher recycling efficiency.
Regular trash bins and Big Belly Trash Bins lack the capability to differentiate recyclables from other waste. As a result, they limit the recycling process by forcing trash companies to transport the waste from these bins to get sorted before the recycling process can begin. Additionally, regular trash bins cannot protect their contents from rodents. Regular trash bins are often old, rusty, and lack covers so waste is often discarded on the streets and subways. In the last decade, their population has skyrocketed to 3 million.
TrashScans smart recognition technology is able to instantly detect and categorize different types of materials and waste. It will automatically sort useful recyclable materials such as plastics, glass, metal, and paper. Waste is thrown into the system and laid onto a moving conveyor belt. Cameras powered by AI use advanced algorithms to identify and sort materials and waste. After identification mechanical claws are used to move the waste and materials into different bins. TrashScan comes equipped with five different trash bins which allow each material to follow in its own bin. This prevents the contamination of materials and allows them to be used again instead of being destroyed.
This project aims to raise consumer awareness about responsible waste disposal and environmental sustainability. We should also remember that failure to adopt innovative solutions will keep waste management systems outdated and less effective as time passes. To manage costs, we propose a phased rollout, starting with high-traffic areas such as schools, public parks, and busy districts. This approach ensures early success and measurable impact, which can justify further investments and potentially attract private funding or public-private partnerships to expand our program.
Credentials
TrashScan is honored to specialize in developing smart systems that integrate AI, sensors, and robotics that relate to environmental sustainability. Saif, our team leader and editor, is pursuing a degree in Environmental Engineering. He is also proficient in reviewing, editing, and refining technical proposals to ensure professionalism and clarity. Timothy, our team editor, is experienced in project management skills such as planning and managing project timelines and budgets. He is our analytical expert, as he is skilled in assessing project flow and ensuring all sections integrate correctly. Mohamed’s responsibility is to identify and anticipate potential challenges to project success by compiling and presenting evidence-based arguments to address our objectives. Raul specializes in design engineering with hands-on experience in CAD and 3D modeling and is skilled in conceptualizing and detailing technical designs for efficient problem-solving.
Deliverables
When creating the TrashScan we had numerous goals including:
Create a simple-to-use design for both users of TrashScan and our customers who deploy TrashScan.Create a motion-activated door that opens when a user is standing in front of the unit for at least 3 seconds and closes after garbage is disposed of.The door closes and locks itself until the sorting cycle is done(usually 30 seconds).Create a cost-effective and competitive system to existing solutions such as the BigBelly Trash Cans, with numerous benefits that our design provides:Current BigBelly trash bins are great for providing an experience that is clean and not as messy as other options for users. These BigBelly trash bins however do not address the issue of the build-up of recyclable materials in landfills.The Design of the TrashScan improves on previous solutions by automating the sorting process of waste which has shown to have disastrous effects on current waste management solutions when compared to other solutions.Develop a design that simplifies the process of recycling to allow for the generation of profits through the sale of recyclable materials including paper, metals, plastics, and glass by sorting different recyclable materials into bins.
Develop a waste management system inside the machine that allows for garbage to be properly managed.A conveyor belt that initially holds all the waste when inserted into the machine and disposes of any waste remaining after sorting is complete4 Mechanical Claws that can sift through the recyclables and move inside the unit to sort recyclables into their proper bins depending on the material.Advanced sensor suite that can properly scan and intelligently command the entire operations of the Device.
Develop robust software tools that allow our customers to easily manage their fleets of TrashScans:Create an integrated software system that allows for wireless communication with each TrashScan device providing data on required maintenance, trash bin capacity, recycling bin capacity, and overall operating data to maximize ease of use.
- Create an advanced power solution that allows for the TrashScan to be connected to the grid or operate using supplemental power provided by an integrated solar panel.
- Advanced Combined Software and Sensor system that allows TrashScan to be able to combine the data from multiple sensors to create an internal picture of the available recyclables including:
- AI-supported recognition Algorithm that controls the claw mechanism optimizing their movements to be able to most efficiently organize recyclables.
- NIR Spectroscopy system that by utilizing infrared radiation, emits infrared light at each item in our conveyor system. Each item reflects a different wavelength of length based on its composition, which the computer analyzes against a known database of values to identify the item.
- Generic Air Freshener System: Maintain the cleanliness and aromatics of each machine/sanitization
- LIDAR: Takes multiple measurements of the items and creates a 3D scan of it
- Camera: More data for AI recognition (shape, 3D orientation, etc)
- AI-powered Raspberry Pi / Nvidia Jetson Nano Dev Kit: Provide computational power to the system power connecting sensors and powering neural networks.
Technical Description
The TrashScan is a uniquely designed device in the world that harnesses brand-new technology powered by AI and can sort and manage different kinds of materials. Inside the device are several systems including a door capable of opening, closing, and locking itself, an advanced sensor suite, and multiple mechanical parts including a conveyor belt, a trash guard, and a gantry to achieve the machine’s goal of sorting materials.
The TrashScan unit is 3 feet wide, 4 feet tall, and 4 feet long
Solar Panel: Provides Power to Unit
Self-Opening Door: Automatically opens according to user presence
Electronics Acces Door: Allows access to electronics for maintenance
Trash Bin Access Door: Allows access to Trash Bin
Metal Bin: Stores Metal recyclables
Glass Bin: Stores Glassrecyclables
Plastic Bin Stores Plastic recyclables
Paper Bin: Stores Paper and Cardboard recyclables
Recyclables Access Door: Allows access to recyclable Bins for maintenance
Conveyor Belt: Moves garbage into trash bin after sorting
Electronics Box: Contains all the sensitive electronics
Trash Bin: Holds the leftover trash after sorting
Trash Guard: Holds garbage in place when doors open and folds down to provide a ramp for garbage to move along
Gantry System: Move along the top inside the unit allowing the Mechanical claws to move
Mechanical Claws: Carry recyclables from the conveyor belt to the recycling bins
Timeline and Budget
| ACTION ITEM | DATE |
| Presentation | January 22, 2025 |
| Research | March 19th, 2025 |
| AI Software Model Training | June 11, 2025 |
| Mechanical Assembly | July 2, 2025 |
| Mass Production | September 10, 2025 |
| Soft Launch | October 1, 2025 |
| Launch | October 15, 2025 |
| TOTAL: | 38 weeks |
Annually, the Department of Sanitation spends 55.9 million dollars on waste export and recycling processing, highlighting the high financial cost of our current waste-management system. TrashScan’s smart recycling offers a cost-effective and efficient system while minimizing long-term recycling costs. Below is the breakdown for the pricing of our unit:
- Aluminum ($420)
- 3D prints of internals ($25-50)
- AI-powered Raspberry Pi / Nvidia Jetson Nano Dev Kit ($45-$220)
- Custom arm attachments, solar panel attachment, conveyor ($700)
- LIDAR & Camera ($200)
- Infrared Sensors ($30)
- Power Supply ($300)
Default trash cans utilized in New York City cost approximately $1,000, while alternatives such as BigBelly range from $3,500-$6,000, which do not include recycling capabilities. The total cost per TrashScan unit is estimated to be approximately $1720-1920, and each unit will retail for approximately $3500, priced competitively with other smart-trash can alternatives. By launching on a similar scale to the 670 BigBelly containers in use in New York City, the total cost upon launch is approximately $2.35 million. However, this projected value is only 53.8% of the city’s current spending on BigBelly trash bins and merely 4.2% of the Department of Sanitation’s annual waste management expenses.
After our thirty-eight-week rendition process, TrashScan will save the Department of Sanitation over 30 million dollars, given the current rate of $433 per ton to process recyclable and non-recyclable waste, and is projected to double the recycling rate.
Conclusion
With the implementation of TrashScan smart recycling, the Department of Sanitation will have access to an autonomous, self-sufficient system that far exceeds the recycling capabilities of current BigBelly containers. Through the usage of solar panels and a mixture of standard and 3D printed components, TrashScan aims to minimize the impact on local electrical grids and ensure maintenance is straightforward and affordable, maintaining the self-autonomy of TrashScan units. In addition, the self-sanitizing component of each unit reduces the olfactory and bacterial effects on users and members of the community. Furthermore, TrashScan’s comprehensive data analytics would allow the DSNY to track the trends of waste collection and the breakdown of recyclables in each implemented district. Through these insights, the DSNY can take action to advocate for increased waste management initiatives at problem locations, as well as optimize recycling routes. With the increased efficiency of TrashScan in both overall recycling as well as waste management, the DSNY can save approximately 30 million dollars per year, which can be reallocated. Moving forward, TrashScan aspires to implement our services in third-world countries, where industrial restraints prevent proper recycling initiatives.
References
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