Abstract algorithms that can be easily implemented. Key Words:

Abstract
– At present waste
management is a major concern in the metropolitan cities of the developing and
developed countries. As the population is growing, the garbage is also
increasing day by day. Garbage management is
becoming a global problem. Due to the lack of care and

attention by the
authorities the garbage bins are mostly seem to be overflowing. It has to be
taken into care by corresponding authorities and should think what method can
be followed to overcome this. This
huge unmanaged accumulation of garbage is polluting the environment, spoiling
the beauty of the area and also leading to the health hazard. To overcome this
situation an efficient smart municipal waste management system has to be
developed. In this era of Internet, Internet of Things (IOT) can be used
effectively to manage this waste as many effective methods can be found out
easily. This is the survey paper which involves the various ideas to solve this
problem using some algorithms that can be easily implemented.

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Key Words: Internet of things (IOT), Smart
Garbage collection.

 

1. INTRODUCTION

 

Now-a- days
smart cities represents hot topic in terms of improving living conditions. As one of the application of Smart City, Waste
Management in a city is a formidable challenge faced by the public
administrations.
IoT is a network of sensors where data is
exchanged, using different connectivity protocols, with systems.
 Waste is defined as any material in which something valuable is not
being used or is not usable and represents no economic value to its owner, the
waste generator. Depending on the physical state of the waste, they are
categorized as solid waste and wet waste. With the proliferation of population,
the scenario of cleanliness with respect to waste management has become
crucial. Waste management includes planning, collection, transport, treatment,
recycle and disposal of waste together with monitoring and regulation. The
existing waste management system, where the garbage is collected from the
streets, houses and other establishments on quotidian basis, is not able to
effectively manage the waste generated. Our work focuses on the
optimization algorithms for Smart City management and more specifically this
paper deals with municipal waste collection procedure. Nowadays,
the garbage-truck needs to pick-up all garbage cans even if they are empty. To
avoid such challenges faced we are proposing a system where efficient routes
are defined shortest route to collect the garbage filled bins.

 

2.1 RECENT RESEARCH IN MUNICIPAL WASTE COLLECTION
OPTIMIZATION

The constant growth of
population urban areas brings increasing municipal solid waste generation with
socio-economic and environmental impact. Municipal solid waste management –
source separation, storage, collection, transfer and transportation, processing
and recovery, and last but not least, disposal, are today current city
challenges. The mathematical programming and processes have been already used
for optimizing the municipal waste management and transfer system. The waste
collection and garbage-truck allocation problem could be solved by traditional
mathematical methods such a linear methods. However, the linear methods show
insufficient efficiency in some more difficult cases of waste collection. The
large amount of variables was the reason for large computation time. The recent
research works use mostly the heuristic solutions and methods dealing with the
municipal waste collection as with a Travelling Salesman Problem (TSP). Dealing
with problem formulation, the effectiveness of optimization and computation is
based on input parameters and specific problem implementation. Only few works
tried to use evolutionary algorithm to deal with implementation and
optimization of waste collection problem as the TSP defines. These works use Ant
Colony algorithm. However, the genetic algorithm was also proven as a very effective
tool to deal with TSP of various implementations, but not in the specific
implementation of waste collection 4.

 

2.2 CHALLENGES

 

2.2.1 Challenges
faced while working with wireless sensor networks (WSN)

1.
Energy – Sensors require power for various operations.
Energy is consumed in data collection, data method, and

data communication.

 

2. Self-management – Once
when WSN are deployed it should be capable of working without help of human intervention.

 

3. Security – Confidentiality
is required while data transmission otherwise there is possibility of
eavesdropping attack.

 

4.
Quality of Service – Quality of service is the level of service
provided by the sensor networks to its users. WSN are being used in various
real time applications, so it is mandatory for the network providers to offer sensible
QoS.

 

5. Fault
Tolerance – Sensor network should be able to work even if any node fails whereas the
Network is operational. Network should be in a position to adapt by changing its
property in case of any difficulty.

 

6.
Limited Memory and Storage Space – A sensor is a small
device with low quantity of memory and storage space for the code. In order to
make an effective security mechanism, it is necessary to limit the code size of
the security algorithm.

 

 

2.3 PATH
OPTIMIZATION TECHNIQUES

 

Optimization
and route planning is a well-researched area and many of the transport systems
have been developed before. There are many projects which provides effective
system for waste management. One of the 
advanced routing model proposed in eastern Finland, they used guided
variable neighbourhood thresholding meta heuristic approach. Garbage truck
scheduling model for solid waste management has been proposed by the city of
Porto Alegre in Brazil. In one of the paper novel cloud based approach is employed.
A new
method for optimizing the waste collection routes is developed based on OSGeo
software tools. Some of the path optimization techniques
has been used there are as follows:

.

 

Table
-1: Path
Optimization Techniques

 

Path optimization Techniques

1.  ArcGIS Network Analyst and Ant Colony

Based
on Geo referential spatial
Database.
Facilitate modelling of realistic traffic condition and different scenarios.
 

2. MapInfo

It is 
GIS software used for finding shortest path

3.
OS Geo software tool

Route planning and optimization software.

 

 

 

 

3. DIFFERENT APPROACHES  AND ALGORITHMS

 

 

Fig -1: System Overview

 

There are some different
approaches in paper 9 the proposed system was based on waste data level of
garbage bins in metropolitan areas. The data was sent over the internet for
analyzing and processing. Everyday new data was collected and on that basis the
rate of waste level was calculated so as to predict the overflow of bins
before. Fig 1. Gives the overview of this approach.

 

Algorithms
used in previous papers for research work was done.

 

3.1    XML Parsing used for graph processing –

The XML parsing is used for
the graph (SVG) processing. After XML parsing.

 

3.2    Floyd- Warshall algorithm

 

 The Floyd- Warshall
algorithm is applied to distance recalculation. This algorithm was chosen due
to the fact that we are using metric system and there the negative values of
edges are not used. The algorithm (Floyd-Warshall) also computes straight the
vertices distance, which is less time consuming than i.e. Dijkstra Algorithm
(which computes distances always for each vertex).

 

2.2.3 PROPOSED
APPLICATIONS

 

1. Waste Level detection inside the garbage
bins.

Transmission of the information wirelessly to

concerned officials.

2. System can be accessed anytime and from

anywhere.

3. Real-time data transmission and access.

4. Avoids the overflows of garbage bins.

5. This project can only be used by municipal

authorities or other private firms to tackle the

current problem of urban waste collection.

6. This system has no individual use, but can be
used

by a city, state or a country.

7. Using this system, waste collection would
become

efficient and also reduction in transportation
costs

can be witnessed.

 

 

5. CONCLUSIONS

 

 This survey has been performed for collecting
the details of smart garbage management methods and to find out effective
methods which are useful for providing hygiene environment in cities. Our
solution is based on the idea of IoT infrastructure, which should provide
enough information to handle this Smart City issue more efficiently.

 

 

6.
REFERENCES

 

1     InsungHong, SunghoiPark,
BeomseokLee, JaekeunLee, Da ebeomJeong, and SehyunPark, “IoT-Based Smart
Garbage System for Efficient Food Waste management” -Scientific World
Journal-Aug 2014.

2     Ala Al – Fuqaha, Mohsen Guizani, Mehdi Mohammadi,
Mohammed Aledhari, Moussa Ayyash, “Internet of Things: A Survey on Enabling
Technologies, Protocols and Applications” IEEE – 2015.

3     TheodorosAnagnostopoulos ,ArkadyZaslavsky, Alexey
Medvedev , “IRobust Waste Collection exploiting Cost Efficiency of loT
potentiality in Smart Cities” – IEEE – April-2015.

4     Radek Fujdiak, Pavel Masek,
Petr Mlynek, Jiri Misurec, “Using Genetic Algorithm for Advanced Municipal
Waste Collection Management in Smart City”, 2016.

5     Vikrant Bhor1, Pankaj
Morajkar2, Maheshwar Gurav3,

Dishant Pandya4, Amol
Deshpande, “Smart Garbage

Management System” – March
2015.

6     Dario Bonion, Maria
Teresa Delgado Alizo, Alexandre

Alapetite, Thomas
Gilbert, MathaisAxling, HelenUdsen,

Jose Angel Carvajalsoto,
Maurizio Spirito,

“ALMANAC: Internet Of
Things for Smart Cities”  IEEE 2015.

7   FachminFolianto, Yong Sheng Low,Wai Leong
Yeow,

       “Smart
bin: Smart Waste Management System”

       
IEEE – April 2015.

8   KristýnaRybová, Jan Slavík, “Smart cities and
ageing

Population – Implications
for waste management in            the Czech
Republic ” – IEEE 2016.

 

9   Jose M. Gutierreza,
Michael Jensenb, Morten Heniusa

      and
Tahir Riazc, “Smart Waste Collection System Based

      on
Location Intelligence” – 2015.

10 Álvaro Lozano Murciego,
Gabriel Villarrubia González,

Alberto LópezBarriuso,
Daniel Hernández de La Iglesia,      Jorge
Revuelta Herrero and Juan Francisco De Paz

Santana, “Smart Waste
Collection Platform Based on

WSN and Route
Optimization ” – 2016.

11   Clarabellejoanna
,Sathiyavathi.R, “Quota based routing

protocol in disruption
tolerant networks”, in    International
conference on information communication embedded systems (icices2014)” , Isbn
no.978-1-4799-3834-6/14©2014.

12    Prakash Prabhu.”IOT based waste management
for 

        
Smart cites” IJECS Vol. 4, Issue 2 FEB 2016.

13 Monika K, Smart
Dustbin- “An Efficient Garbage           Monitoring System”. IJECS Volume 6 Issue No.
06 June 2016.

 

 

 

 

 

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