An IoT based Architecture for Waste Management

1. Report On
An IoT-based Architecture for
Waste Management
International Islamic University
Chittagong
Department Of C.S.E
Author:
Nusrat Alam
C161271
5CF
Date of submission:
December 19, 2018
Supervisor:
Sanjida Sharmin
Lecturer
Dept. of CSE, IIUC

2. Contents
1 Abstract 2
2 Introduction 3
3 Related work 4
4 Main features and scenarios of usage 4
5 Waste Management : 6
5.1 Smart Waste Bin Technology and Services . . . . . . . . . . . . . 6
5.2 Mobile Application . . . . . . . . . . . . . . . . . . . . . . . . . . 7
5.3 The Driver Module . . . . . . . . . . . . . . . . . . . . . . . . . . 8
5.4 The Cloud Server . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
5.5 Route-planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
6 Conclusion 10
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3. 1 Abstract
Efficient waste collection is a necessary service in the application of Smart Cities.
The use of emerging technology may lead to significant improvement in the waste
management process. In this work, we propose an IoT-based architecture that
targets two elements. The first is monitoring the waste volume and content in
a waste bin, as well as the bin’s surroundings.
The second entails dynamic scheduling and routing of waste collection vehicles
based on the relayed information from the bins. The waste bin design detects
any obstacles around the bin and monitors illegal dumping in the vicinity of the
bin. The routing protocol provides an optimal solution for waste collection from
the filled bins in high density residential areas while minimizing the length of
the trip. The combined improvement of these elements will result in increasing
the efficiency of waste collection, reducing and carbon footprint.
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4. 2 Introduction
Proper waste management is an integral aspect ofcity management. Continuous
development efforts lead to employing novel technology to reduce operational
cost while maintaining consistent levels of service.
Current waste collection efforts utilize static route planning with fixed schedul-
ing, which indicates there still exists areas for continued development and im-
provement in this field.. Such an approach is costly and generates a high-carbon
footprint. The slow adoption of recycling in some cities also continues to result
in monetary losses. The lack of recycling in Saudi cities, for example, is esti-
mated to result in 40 billion SAR ( 10.6 billion) per year in losses [1].
Meanwhile, the absence of waste monitoring and limited waste-bin allocation
per household may lead the public to overfill their bins or discard waste in non-
designated areas. The city may thereby incur additional costs for the added
demand for waste removal and management.
The latter is most pronounced in areas with strained infrastructure, such as
restaurant clusters or narrow pathways between houses. Bursts in waste gener-
ation, such as those following national holidays, can also generate a widespread
high demand for waste collection.
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5. 3 Related work
The area of route planning and optimizing for logistic purposes is well-researched
and hun-dreds of Intelligent Transportation Systems already exist.
There are also a number of pro-jects aiming to provide an effective system
specializing on waste collection needs. A Geo-graphical Information System
(GIS) transportation model for solid waste collection that elaborates plans for
waste storage, collection and disposal has been proposed in [2] for the city of
Asansol in India.
In [3] an enhanced routing and scheduling waste collection model is proposed
for the Eastern Finland, featuring the usage of a guided variable neighbourhood
thresholding metaheuristic. In the city of Porto Alegre in Brazil authors propose
[4] a truck-scheduling model for solid waste collection. The aim of the research
was to develop an op-timal schedule for trucks on defined collection routes.
Examples of other systems are de-scribed in [5],[6],[7] and [8].
4 Main features and scenarios of usage
System architecture aims to suit two main targets. First target is providing
software-as-a-service (SaaS) products for customers. Mainly, these customers
are private companies that are involved in waste collection, owning waste trucks,
organize work of drivers, get con-tracts from municipalities and pass wastes
to recycling organizations or city dumps. Second main target is developing a
system, which makes possible mutually beneficial communica-tion between all
the stakeholders involved in the chain of supplying goods and utilizing solid
waste in smart city.
Figure 1: The big picture of a waste collection management system
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6. A list of possible stakeholders of the system and brief description of their
needs, business rules, possibilities and connections with others is presented be-
low:
1. City administration needs understanding of the big picture, generating re-
ports, control over pricing etc.
2. District administrations are interested in controlling the process of waste
collection, checking quality of service (all waste collected, all in time, waste
collected cleanly, waste transported to special places), quick and legal ways for
solving disputes and problems. Municipalities can also deploy and maintain
smart city infrastructure like capacity sen-sors in waste bins and wireless net-
works for data transferring.
3. Waste trucks owning companies need platform for organizing and optimiza-
tion of their business process in general without serious investments in devel-
oping, deploying and supporting their own system. Such system must include
effective dynamic routing based on IoT data for the truck fleet. Besides, con-
trolling drivers and tracking the fleet is also an important issue.
4 .Waste truck drivers need navigation system for fulfilling their tasks. An-
other issue is reporting problems and passing them to the operators in the office
instead of thinking how to solve the problem, this can sufficiently save time
of a driver and vehicle. Drivers also need evidence that their work was done
correctly and cleanly.
5 .Managers of dumps and recycling factories can publish their possibilities
or needs in acquiring certain amount of waste for storing or recycling
6 .Staff that is responsible for trash bins in the current yards needs commu-
nications with waste management companies and truck drivers.
7. Road police can get reports about inaccurate car parking that leads to
impossibility of waste collection.
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7. 5 Waste Management :
5.1 Smart Waste Bin Technology and Services
The smart-waste bin component of the architecture is responsible for updat-
ing the architecture components on its contents volume and type, as well as its
surroundings. The smart waste-bin is equipped with a mix of sensors that facili-
tates both sensing and communication to the cloud. The target implementation
comprises a microcontroller, such as an Arduino Yun or a lattepanda board.
The microcontroller provides management to several connected sensors. Sensor
choice depends on the implementation objective and configuration. A certain
design instance detailed here assumes a basic implementation which includes
the minimum necessary combination for our considerations. These include the
following components and sensors: 1. Three 5m proximity sensors;
2. High capacity load cell;
3. Humidity sensor;
4. Lever activated switch;
5. GPS; and
6. Microcontroller.
Figure 2: A schematic of the proposed IoT-based waste management archi-
tecture, showing the interconnectivity between the smart bins, the collection
vehicles and the cloud.
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8. 5.2 Mobile Application
The mobile app is used by municipal waste disposal vehicle drivers to identify
the route and scheduled bin location. The mobile app functions as a point of
connection between the driver and the cloud. Additionally, the mobile app can
be installed by the residential crowd to control dumping allowances per user
or household. QR code technology at the bin is implemented to only allow
registered users to use the bin. Users scan the QR code using the app to unlock
the bin. The bin measures the waste weight at each usage for recording purposes.
Figure 3: An illustration of the component and sensor placement on the waste
bin. (Front View).
Figure 4: An illustration of the component and sensor placement on the waste
bin. (Side View).
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9. 5.3 The Driver Module
The driver module ensures dynamic routing implementation by continuously
monitoring the driver speed, location, and waste level in the truck. The latter
data can be
crucial in dynamic routing to maximize the number of bins collected by a single
vehicle and minimizing incurred cost and potential carbon footprint. This sen-
sory data is collected by the truck OBDII and sent to the drivers’ mobile app
via Bluetooth dongle, which sends it in turn to the cloud to dynamically update
the collection route when necessary. Data fusion of the sensory data from the
OBDII with that of the mobile (speed, location) can be utilized to improve the
accuracy of the collected data.
5.4 The Cloud Server
The cloud is the main processing unit of the system. Data is aggregated from
end-users’ apps and drivers, weather condition, current sport and celebration
events with a potential effect on waste truck routing or waste amount (month
of Ramadan at night), traffic rush hour, and each bin’s surrounding environ-
ment. Our proposed system reacts actively to the triggering events of waste
collection by analyzing data from waste bins and drivers’ apps to optimize the
waste collection routes. For example, the system can react to traffic rush hour
by avoiding waste collection from these areas during this period.
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10. 5.5 Route-planning
complicates the route-planning and collection scheduling without justification.
Consideration for aggregating the states of the smartbins
based on area or route-access thus becomes inevitable. Such considerations
would include a pre-processing of the roadnetwork model (or graph) in order
to identify the shortest path between main area clusters. This pre-processing
would be similar to that performed in solving VRP problems, but with the
effects of time-of-the-day, weather, traffic, and others taken into account.
Figure 5: The result of the VRP solvation
Reducing cost and environmental impact of waste collection will depend
on optimizing the system by observing long-term trends in waste collection and
anticipating future challenges due to increased demand or special circumstances.
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11. 6 Conclusion
This paper presents an architecture based on IoT with the objective of im-
proving waste management systems. Our approach is a holistic review of the
waste management system, starting from smartening-up the waste-bin to op-
timize waste collection times and anticipating the nature of collected waste to
considerations of the collection vehicles, their route planning and scheduling.
The presented architecture depended on a cloud-based implementation for the
processing and computation core.
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12. References
[1] ”Lack Of Recycling Costs Kingdom SR 40 Bn A Year”. 2017. Arab News.
http://www.arabnews.com/lack-recycling-costs-kingdom-sr- 40-bn-year.
[2] Ghose M. K., Dikshit A. K., S. K. Sharma, A GIS based transportation
model for solid waste disposal A case study on Asansol municipality”, Jour-
nal of Waste Management, vol. 26 (11), pp. 1287-1293, January, 2006.
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scheduling of waste collection and transport”, Journal of Expert Systems
with Applications, vol. 30 (2), pp. 223-232, February, 2006.
[4] Li J. Q., Borenstein D., Mirchandani P. B., Truck scheduling for solid waste
collection in the City of Porto Alegre, Brazil”, Journal of Omega, vol. 36
(6), pp. 1133-1149, December, 2008.
[5] Zamorano M., Molero E., Grindlay A.,A planning scenario for the ap- pli-
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[6] Tavares G., Zsigraiova Z., Semiao V., Carvalho M. G., Optimisation of
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eling”.
[7] Benjamin A. M., Beasley J. E., Metaheuristics for the waste collection
vehicle routing problem with time windows, driver rest period and multiple
dis- posal facilities”.
[8] Son L. H., Optimizing Municipal Solid Waste collection using Chaotic Par-
ticle Swarm Optimi-zation in GIS based environments: A case study at
Danang city, Vietnam”, Journal of Expert Sys-tems with Applications,
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