ABSTRACT-A “Smart City” generally means a technologically advanced city that is able tounderstand its environment through analyzing its data so that it immediatelymakes changes to solve issues and to improve the residents’ quality of life.
The huge volume, high velocity and wide variety of city’s data require theutilization of “Big Data” technologies to gain valuable insights from it. The concept of the smart city is widelyfavored, as it enhances the quality of life of urban citizens, involvingmultiple disciplines, that is, smart community, smart transportation, smarthealthcare, smart parking, and many more. This paper reviews theapplications and, hence, the potentials where Big Data technology can drive acity to be smart. Starting from investigating the visibility of the city, whichmeans collecting data from all networks, devices and sensors thatembedded in its infrastructure.
Continuing to explain how can this data becomevaluable by passing different processing stages, and by applying advancedanalyzing Big Data platforms on data? The smartness of the data driven city isachieved by visualizing the data in useful shape in order to improve any city’ssystem application. The literature review also shows the practical applicationsof Big Data in a Smart City in the domains of smart energy, smart public safetyand smart traffic systems. INTRODUCTIONSmart cities faceserious challenges prior to widespread acceptance, but their integrated use ofBig Data, and other technologies to solve contemporary urban issues shouldeventually lead to their adoption.
Big data offer thepotential for cities to obtain valuable insights from a large amount of datacollected through various sources, and the IoT allows the integration ofsensors, radio-frequency identification, and Bluetooth in the real-worldenvironment using highly networked services. Thecombination of the IoT and big data is an unexplored research area that hasbrought new and interesting challenges for achieving the goal of future smartcities. These new challenges focus primarily on problems related to businessand technology that enable cities to actualize the vision, principles, andrequirements of the applications of smart cities by realizing the main smartenvironment characteristics.The concept of smart cities (SC) emerged as astrategy to mitigate unprecedented challenges of continuous urbanization, whileat the same time provide better quality of life to the citizens. City smartnessis realized by means of the advances of Information and CommunicationTechnologies (ICT) and as a result SCs are usually characterized by anextensive use of digital technologies in various city domains in combinationwith a holistic view of the city where different domains should be closedintegrated.
This article is a systematic literature review onBIG DATA ANALYTICS frameworks in SCs aiming at answering three basic researchquestions. RQ1: What types of BIG DATA ANALYTICS frameworks are available forthe smart city context? RQ2: What are the functional gaps in the currentavailable frameworks? Finally, RQ3: What conceptual guidelines for designingintegrated scalable BIG DATA ANALYTICS frameworks, relevant for smart citycontexts, can be found in the literature? The literature review analyzed 10articles addressing BD applications in SCs. I. WHAT IS BIGDATA?The term Big Data refers to all the data that is being generated acrossthe globe at an unprecedented rate. This data could be either structured orunstructured.
Today’s business enterprises owe a huge part of their success toan economy that is firmly knowledge-oriented. Data drives the modern organizations of the world and hence making sense of this data andunraveling the various patterns and revealing unseen connections within thevast sea of data becomes critical and a hugely rewarding endeavor indeed. Thereis a need to convert Big Data into BusinessIntelligence that enterprises can readily deploy. Better dataleads to better decision making and an improved way to strategize fororganizations regardless of their size, geography, market share, customersegmentation and such other categorizations.
Hadoopis the platform of choice for working with extremelylarge volumes of data. The most successful enterprises of tomorrow will be theones that can make sense of all that dataat extremely high volumes and speeds in order to capturenewer markets and customer base. Ø 5 V’S OF BIG DATA:- Big Data has certain characteristics and hence is defined using4Vs namely: Volume: The amount of data that businesses can collect isreally enormous and hence the volume of the data becomes a critical factor in Big Data analytics. Velocity: The rate at which new data is being generated allthanks to our dependence on the internet, sensors, and machine-to-machine datais also important to parse Big Data in a timely manner.Variety: Thedata that is generated is completely heterogeneous in the sense that it couldbe in various formats like video, text, database, numeric, sensor data and soon and hence understanding the type of Big Data is a key factor to unlocking its value.Veracity: Knowingwhether the data that is available is coming from a credible source is ofutmost importance before deciphering and implementing Big Data for businessneeds.Value: Last but not least, big data must havevalue.
That is, if you’re going to invest in the infrastructure required tocollect and interpret data on a system-wide scale, it’s important to ensurethat the insights that are generated are based on accurate data and lead tomeasurable improvements at the end of the day. Ø BIGDATA TECHNOLOGIES:- Bigdata is an evolving term that describes any voluminous amount ofstructured, semi structured and unstructured data that has thepotential to be mined for information.Big data technologies are important in providing moreaccurate analysis, which may lead to more concrete decision-making resulting ingreater operational efficiencies, cost reductions, and reduced risks for thebusiness.To harness the power of big data, you would require aninfrastructure that can manage and process huge volumes of structured andunstructured data in realtime and can protect data privacy and security. Some technologies used for big dataanalytics:-1. Hadoop: – Hadoop is an Apache open sourceframework written in java that allows distributed processing of large datasetsacross clusters of computers using simple programming models.
A Hadoopframe-worked application works in an environment that provides distributedstorage and computation across clusters of computers. Hadoop is designed toscale up from single server to thousands of machines, each offering localcomputation and storage. 2. MongoDB: – MongoDBis an open-source document database that provides highperformance, high availability, and automatic scaling. MongoDB obviates theneed for an Object Relational Mapping (ORM) to facilitate development.
3. MapReduce: – MapReduce is a programming model for writing applications thatcan process Big Data in parallel on multiple nodes. MapReduce providesanalytical capabilities for analyzing huge volumes of complex data. MapReducedivides a task into small parts and assigns them to many computers. Later, theresults are collected at one place and integrated to form the result dataset.
4. Hive:- Hiveis a data warehouse infrastructure tool to process structured data in Hadoop.It resides on top of Hadoop to summarize Big Data, and makes querying andanalyzing easy.
Initially Hive was developed by Facebook, later the ApacheSoftware Foundation took it up and developed it further as an open source underthe name Apache Hive. It is used by different companies. For example, Amazonuses it in Amazon Elastic MapReduce. 5. Apache Pig:- Apache Pig is an abstraction over MapReduce. It is atool/platform which is used to analyze larger sets of data representing them asdata flows. Pig is generally used with Hadoop; we can perform all the datamanipulation operations in Hadoop using Pig.
II. WHAT IS ASMART CITY?A smartcity is an urban area that uses different types of electronicdata collection sensors to supply information used to manage assets andresources efficiently. This includes data collected from citizens,devices, and assets that is processed and analyzed to monitor and managetraffic and transportation systems, power plants, water supply networks, wastemanagement, law enforcement, information systems, schools, libraries,hospitals, and other community services.
The smartcity concept integrates information andcommunication technology (ICT),and various physical devices connected to the network (the Internet of things or IoT) to optimize theefficiency of city operations and services and connect to citizens. Smartcity technology allows city officials to interact directly with both communityand city infrastructure and to monitor what is happening in the city and howthe city is evolving.Visionof smarter cities:-–Environmental sustainability and efficiency–Sustainable homes and buildings–Efficient use of resources–Efficient and sustainable transportation– Betterurban planning – livable citiesSmartCity Applications:-· Smart parking:Monitoring of parking spaces availability in the city. · Structural Health:Monitoring of vibrations and material conditions in buildings, Bridges andhistorical monuments. · Noise Urban maps:Sound monitoring in bar areas and centric zones in real time.
· Smartphone detection:Detect smart phones and in general any device which works with Wifi orBluetooth interfaces. · Electromagnetic field levels: Measurement of the energy radiated by cell stations and WiFirouters. · Traffic Congestion:Monitoring of vehicles and pedestrian levels to optimize driving and walkingroutes. · Smart lighting:Intelligent and weather adaptive lighting in street lights. · Waste management:Detection of rubbish levels in containers to optimize the trash collectionroutes. Smart roads: Intelligent Highways with warning messages and diversions according to climate conditions and unexpected events like accidents or traffic jams.