The problem TrashTracker solves

Here are 5 practical uses for the IoT-based smart waste management system, as well as how it may make current operations simpler and safer:

1. Effective Waste Management: The system optimizes the procedures for garbage disposal and collection, which requires less manual intervention. This decreases the danger of damage to waste management workers while also conserving resources and time.

2. Real-Time Monitoring: The technology enables quick and effective reaction to overflowing bins by allowing real-time monitoring of garbage levels. This prevents the transmission of infections by keeping the environment hygienic and clean.

3. Waste Segregation: The method aids in the correct categorization of garbage into several streams, making it simpler to handle and get rid of. This encourages citizens to dispose of rubbish responsibly and minimizes the detrimental effects on
   the environment.

4. Analysis of data: The system gathers data on waste generation trends, offering information that can guide waste management strategies. This lowers the price of waste management and improves resource allocation that is efficient.

5. Sustainable Environment: The system creates a sustainable environment for future generations by encouraging ethical trash proper disposal. This results in a better and cleaner living environment, which enhances general welfare.

Challenges we ran into

Problem 1: While training an ML Model for classification of different wastes and detection of the same was a challenge at first, as understanding high quality datasets and optimizing its hyperparameters requires a lot of computational time.
Solution 1: Using pre-trained models and transfer learning techniques helped to reduce time, then Synthetic Data generation from SVD or Faker module helped us to expand the dataset for improving model performance

Problem 2: After collecting data from various sources, it is our duty to manage it properly and keep it secure. So, in simple words, ensuring data privacy while maintaining accessibility is also a challenge.
Solution 2: We thought of a cloud based storage for data security, or we can also use blockchain for storing data in decentralized manner for preventing misuse of data.

Problem 3: One problem could be the integration of ML models or software with the hardware sensors, microcontrollers, network components for smooth workflow.
Solution 3: Developing communication protocols or using restful APIs can solve the problem as these protocols enable interoperability between different components of the system.