Table of contents
1. Abstract
2. Introduction
3. Methodology
4. key components
5. Block diagram
6. Working principle
7. Pin diagram
8. Output
9. Advantages
10. Conclusion
MINI PROJECT
GARBAGE SEGREGATION (WET AND DRY)
ABSTRACT:
management of solid waste is one of the most pressing environmental
challenges. The accumulator unsegregated waste poses severe threats not
only to public health and safety but also to the sustainability of urban
infrastructure and environmental well-being. A significant part of this
challenge stems from the lack of effective segregation practices at the
source. Despite multiple awareness campaigns and regulatory
frameworks, citizens often fail to comply with proper waste separation
norms. As a result, mixed waste ends up in landfills, causing soil and
water contamination, releasing greenhouse gases, and rendering
recyclable material useless. To address these challenges, this research
focuses on the design and implementation of a smart system capable of
automatically segregating wet and dry waste using Internet of Things
(IoT) technologies and sensor-based system.
Introduction:
Solid waste management has become a critical concern in both
developing and developed countries due to rapid urbanization,
population growth, and changing consumption patterns. Municipal
bodies worldwide struggle to manage increasing volumes of waste,
which often result in environmental pollution, public health hazards, and
unsanitary living conditions. A major challenge in effective waste
management is the improper segregation of waste at the source, where
household and commercial waste generators fail to separate
biodegradable (wet) waste from recyclable and non-biodegradable (dry)
waste.Wet waste typically includes organic matter such as food scraps,
vegetable and fruit peels, and other biodegradable materials, which can
be composted or used for biogas production. On the other hand, dry
waste comprises items like plastics, paper, glass, metals, and other
recyclable materials that can be processed and reintroduced into the
manufacturing cycle. Mixing these two types of waste not only
complicates the recycling process but also results in the contamination
of dry waste, making it unsuitable for reuse and increasing the burden on
landfills.
Methodology:
Step 1: Identify the Types of Waste
*Wet Garbage*: Organic waste, such as food waste, fruit and vegetable
peels, and other biodegradable materials.
*Dry Garbage*: Non-organic waste, such as plastics, papers, metals, and
other non-biodegradable materials.
Step 2: Provide Separate Bins
*Wet Garbage Bin*: Designate a bin specifically for wet garbage, such
as a compost bin or a bin with a lid to prevent odors and pests.
*Dry Garbage Bin*: Designate a bin specifically for dry garbage, such
as a recycling bin or a bin with a separate compartment for different
types of dry waste.
Step 3: Segregate Waste at Source
*Household Segregation*: Encourage households to segregate waste at
source, separating wet and dry garbage into designated bins.
*Community Segregation*: Implement community-level segregation
programs, providing separate bins for wet and dry garbage in public
spaces.
Step 4: Collect and Transport Segregated Waste
*Separate Collection*: Collect wet and dry garbage separately, using
designated vehicles or containers to prevent mixing.
*Transport to Designated Facilities*: Transport segregated waste to
designated facilities, such as composting plants for wet garbage and
recycling facilities for dry garbage.
Step 5: Process and Dispose of Segregated Waste
*Composting*: Process wet garbage through composting, converting
organic waste into nutrient-rich compost.
*Recycling*: Process dry garbage through recycling, converting non-
organic waste into reusable materials.
*Proper Disposal*: Dispose of non-recyclable waste in an
environmentally responsible manner, such as through landfilling or
incineration.
Key components:
1.Moisture Sensor:
Function: Detects moisture levels in waste to distinguish between
wet (organic) and dry (inorganic) items.
2. IR Sensor (Infrared Sensor)
Function: Helps detect the presence of objects and differentiate between
types of materials based on reflectivity. Can help in initial sorting.
3. Load Cell (Weight Sensor)
Function: Measures the weight of waste to, or Raspberry Pi)
4: .microcontroller
Function: Processes data from sensors and controls actuators (like motors
or flaps) to divert waste accordingly.
5. Servo Motor / DC Motor with Flap Mechanism
Function: Physically moves or redirects waste into appropriate bins
based on sensor inputaid in classification and bin management.
BLOCK DIAGRAM:
WORKING PRINCIPLE :
IoT-Based Data Transmission
The bin status and system health information are transmitted in real-time
to a cloud server via a Wi-Fi module (e.g., ESP8266 or NodeMCU). The smart
garbage segregation system operates based on the combined
functionality of sensors, actuators, and a microcontroller unit, which
together automate the process of identifying and sorting waste into wet
and dry categories. The system is designed to handle waste at the point
of disposal and reduce the need for manual segregation, thus improving
efficiency, hygiene, and recycling rates. Moisture Sensing for Wet/Dry
Classification.The waste item first interacts with a moisture sensor that
detects the presence of water content. If the sensor detects high moisture
levels, the item is classified as wet waste (e.g., food leftovers, vegetable
peels).If low or no moisture is detected, the item is temporarily
categorized as dry waste and passed to the next classification phase for
further analysis. Material-Type Detection Dry waste is further evaluated
using capacitive and inductive proximity sensors Capacitive sensors
detect non-metallic dry materials like paper, plastic, or cloth.
Inductive sensors identify metallic objects such as cans, foil, or
batteries.This multi-layer detection ensures improved classification
accuracy and prevents misrouting of complex or composite materials.
Waste Segregation and RoutingOnce the classification is complete, the
microcontroller processes the data and actuates a servo motor or
conveyor-based diverter to guide the waste item to the appropriate
bin:Wet waste is routed to the organic bin, typically meant for
composting or anaerobic digestion.Dry waste is routed to the recyclables
bin, which can later be sorted into specific material types.
Bin Level Monitoring
Each bin is equipped with an ultrasonic sensor to monitor its fill level.
When the waste accumulates to a predefined limit, the sensor sends
distance data to the microcontroller, which calculates the percentage of
bin.
PIN DIAGRAM:
OUTPUT:
DETECT DRY WASTE:
DETECT WET WASTE:
ADVANTAGES:
1.Automatic Waste Segregation
The system eliminates the need for manual segregation by using sensors to distinguish
between wet and dry waste accurately and efficiently.
2.Improved Hygiene and Safety
By reducing human contact with waste, the system minimizes health risks and exposure
to hazardous or infectious materials for sanitation workers.
3.Real-time Monitoring via IoT
With the integration of IoT, authorities can track bin fill levels and receive notifications
when bins are full or malfunction, allowing timely collection and better resource
allocation.
4.Promotes Recycling and Composting
Proper segregation at the source increases the quality of recyclable materials and
ensures organic waste can be efficiently composted or used in biogas production.
5.Environmentally Friendly
The use of solar panels for power supply makes the system energy-efficient and
suitable for sustainable smart city applications.
CONCLUSION:
The increasing complexity and volume of municipal solid waste call for innovative and
efficient waste management solutions. This paper presents a smart garbage
segregation system that utilizes sensor-based automation and IoT technologies to
distinguish between wet and dry waste at the source. By integrating moisture,
capacitive, inductive, and proximity sensors with microcontroller-based control and real-
time IoT monitoring, the system provides a reliable and scalable method for waste
segregation. The system not only reduces human intervention and associated health
risks but also improves the quality of recyclable materials and enhances the composting
process. Real-time bin level monitoring and data transmission ensure that waste
collection can be timely and optimized, thus minimizing overflows and environmental
hazards. Additionally, the potential to operate on solar power makes the system suitable
for sustainable and off-grid applications.
Despite some challenges such as sensor limitations, mixed waste detection, and initial
installation costs, the proposed system shows promising results in terms of segregation
accuracy, response time, and operational efficiency. With further integration of advanced
technologies like AI-based image processing and machine learning, the system can
evolve into a more intelligent and adaptive solution.
