Abstract- At present wastemanagement is a major concern in the metropolitan cities of the developing anddeveloped countries. As the population is growing, the garbage is alsoincreasing day by day. Garbage management isbecoming a global problem. Due to the lack of attention took by the authoritiesthe garbage bins are mostly seem to be overflowing.
It has to be taken intocare by corresponding authorities and should think what method can be followedto overcome this. Thishuge unmanaged accumulation of garbage is polluting the environment, spoilingthe area and also leading to the health hazard. To overcome this situation anefficient smart municipal waste management system has to be developed.
In thisera of Internet, Internet of Things (IOT) can be used effectively to managethis waste as many effective methods can be found out easily. This is thesurvey paper which involves the various ideas to solve this problem using somealgorithms that can be easily implemented. Key Words: Internet of things (IOT), SmartGarbage collection.
1. INTRODUCTION Now-a- dayssmart cities represents hot topic in terms of improving living conditions. As one of the application of Smart City, Waste Managementin a city is a big challenge faced by the public administrations. IoTis a network of sensors where data is exchanged, using different protocols,within systems. Waste is defined as any material in which somewhat valuable is not beingused or is not usable and represents no economic value to its owner, the wastegenerator.
Depending on the state of the waste, they are categorized into drywaste and wet waste. Waste management includes planning, collection, transport,recycle and disposal of waste together with monitoring and regulation. Theexisting waste management system, where the garbage is collected from thestreets, houses and other establishments on quotidian basis, is not able toeffectively manage the waste generated. Our work focuses on theoptimization algorithms for Smart City management and more specifically thispaper deals with municipal waste collection procedure. Nowadays,the garbage-truck needs to pick-up all garbage cans even if they are empty. Toavoid such challenges faced we are proposing a system where efficient routesare defined shortest route to collect the garbage filled bins. 2.
RECENT RESEARCH IN MUNICIPAL WASTE COLLECTIONOPTIMIZATIONThe constant growth ofpopulation urban areas brings increasing municipal solid waste generation withsocio-economic and environmental impact. Municipal solid waste management -source separation, storage, collection, transfer and transportation, processingand recovery, and last but not least, disposal, are today current citychallenges. The mathematical programming and processes have been already usedfor optimizing the municipal waste management and transfer system. The wastecollection and garbage-truck allocation problem could be solved by traditionalmathematical methods such a linear methods. However, the linear methods showinsufficient efficiency in some more difficult cases of waste collection. Largeamount of variables was the reason for large and hard computation time. Therecent research works use mostly the heuristic solutions and methods dealingwith the municipal waste management as with a Travelling Salesman Problem(TSP). Dealing with problem formulation, the effectiveness of optimization andcomputation is based on input parameters and specific problem implementation.
Onlyfew works tried to use evolutionary algorithm to deal with implementation andoptimization of waste collection problem as the TSP defines. These works useAnt Colony algorithm. However, the genetic algorithm was also proven as a very effectivetool to deal with TSP of various implementations, but not in the specificimplementation of waste collection 4. 2.1 CHALLENGES Challengesfaced 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 – Oncewhen WSN are deployed it should be capable of working without help of human intervention. 3. Security – Confidentialityis required while data transmission otherwise there is possibility ofeavesdropping attack. 4.
Quality of Service – Quality of service is the level of serviceprovided by the sensor networks to its users. WSN are being used in variousreal time applications, so it is mandatory for the network providers to offer sensibleQoS. 5. FaultTolerance – Sensor network should be able to work even if any node fails whereas theNetwork is operational. Network should be in a position to adapt by changing itsproperty in case of any difficulty. 6.Limited Memory and Storage Space – A sensor is a smalldevice with low quantity of memory and storage space for the code.
In order tomake an effective security mechanism, it is necessary to limit the code size ofthe security algorithm. 2.2SOLUTIONS · DataFreshness – There should be new messages even if confidentiality is assured. · SecureLocalization – Often, the utility of a device network can trust on itsability to accurately mechanically find every sensor within the network. A sensornetwork designed to find fault scan would like correct location data in order topurpose the placement of a fault.
· Privacy – The sensor networks have conjointly force privacy issues.Privacy play an important role.· Securerouting – Routing and dataforwarding is a crucial service for facultative communication in devicenetworks.· DataAvailability – Availability resolves whether or not a node has the capacityto use the resources and whether or not the network is obtainable for themessages to speak. However, failure of the base station or cluster leader’savailability can eventually threaten the complete sensing element network.Thus availableness is of primary importancefor maintaining associate degree operational network 2.3 PATHOPTIMIZATION TECHNIQUES Optimizationand route planning is a well-researched area and many of the transport systemshave been developed before.
There are many projects which provides effectivesystem for waste management. One of the advanced routing model proposed in eastern Finland, they used guidedvariable neighbourhood thresholding meta heuristic approach. Garbage truckscheduling model for solid waste management has been proposed by the city ofPorto Alegre in Brazil. In one of the paper novel cloud based approach isemployed. A new method for optimizing the waste collection routes is developed basedon OSGeo software tools. Some of the path optimizationtechniques has been used there are as follows: Table-1: PathOptimization 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 differentapproaches in paper 9 the proposed system was based on waste data level ofgarbage bins in metropolitan areas.
The data was sent over the internet foranalyzing and processing. Everyday new data was collected and on that basis therate of waste level was calculated so as to predict the overflow of binsbefore. Fig 1. Gives the overview of this approach.
Algorithmsused in previous papers for research work was done. 3.1 XML Parsing used for graph processing –The XML parsing is used forthe graph (SVG) processing. After XML parsing.
3.2 Floyd- Warshall algorithm The Floyd- Warshallalgorithm is applied to distance recalculation. This algorithm was chosen dueto the fact that we are using metric system and there the negative values ofedges are not used. The algorithm (Floyd-Warshall) also computes straight thevertices distance, which is less time consuming than i.e. Dijkstra Algorithm(which computes distances always for each vertex). 4. PROPOSEDAPPLICATIONS 1.
Waste Level detection inside the garbagebins.Transmission of the information wirelessly toconcerned officials.2. System can be accessed anytime and fromanywhere.3. Real-time data transmission and access.4.
Avoids the overflows of garbage bins.5. This project can only be used by municipalauthorities or other private firms to tackle thecurrent problem of urban waste collection.6.
This system has no individual use, but can beusedby a city, state or a country.7. Using this system, waste collection wouldbecomeefficient and also reduction in transportationcostscan be witnessed. 5. CONCLUSIONS This survey has been performed for collectingthe details of smart garbage management methods and to find out effectivemethods which are useful for providing hygiene environment in cities. Oursolution is based on the idea of IoT infrastructure, which should provideenough information to handle this Smart City issue more efficiently. 6.REFERENCES 1 InsungHong, SunghoiPark,BeomseokLee, JaekeunLee, Da ebeomJeong, and SehyunPark, “IoT-Based SmartGarbage System for Efficient Food Waste management” -Scientific WorldJournal-Aug 2014.
2 Ala Al – Fuqaha, Mohsen Guizani, Mehdi Mohammadi,Mohammed Aledhari, Moussa Ayyash, “Internet of Things: A Survey on EnablingTechnologies, Protocols and Applications” IEEE – 2015.3 TheodorosAnagnostopoulos ,ArkadyZaslavsky, AlexeyMedvedev , “IRobust Waste Collection exploiting Cost Efficiency of loTpotentiality in Smart Cities” – IEEE – April-2015.4 Radek Fujdiak, Pavel Masek,Petr Mlynek, Jiri Misurec, “Using Genetic Algorithm for Advanced MunicipalWaste Collection Management in Smart City”, 2016.5 Vikrant Bhor1, PankajMorajkar2, Maheshwar Gurav3, Dishant Pandya4, AmolDeshpande, “Smart Garbage Management System” – March2015.6 Dario Bonion, MariaTeresa Delgado Alizo, Alexandre Alapetite, ThomasGilbert, MathaisAxling, HelenUdsen, Jose Angel Carvajalsoto,Maurizio Spirito, “ALMANAC: Internet OfThings for Smart Cities” IEEE 2015.7 FachminFolianto, Yong Sheng Low,Wai LeongYeow, “Smartbin: Smart Waste Management System” IEEE – April 2015.8 KristýnaRybová, Jan Slavík, “Smart cities andageing Population – Implicationsfor waste management in the CzechRepublic ” – IEEE 2016. 9 Jose M.
Gutierreza,Michael Jensenb, Morten Heniusa andTahir Riazc, “Smart Waste Collection System Based onLocation Intelligence” – 2015.10 Álvaro Lozano Murciego,Gabriel Villarrubia González, Alberto LópezBarriuso,Daniel Hernández de La Iglesia, JorgeRevuelta Herrero and Juan Francisco De Paz Santana, “Smart WasteCollection Platform Based on WSN and Route Optimization” – 2016.11 Clarabellejoanna,Sathiyavathi.R, “Quota based routing protocol in disruptiontolerant networks”, in Internationalconference on information communication embedded systems (icices2014)” , Isbnno.
978-1-4799-3834-6/14©2014.12 Prakash Prabhu.”IOT based waste managementfor Smart cites” IJECS Vol. 4, Issue 2 FEB 2016.13 Monika K, SmartDustbin- “An Efficient Garbage Monitoring System”.
IJECS Volume 6 Issue No.06 June 2016.