SmartCityFramework

Smart city framework using IoT and Big Data

Abstract

Information and Communications Technology is becoming increasingly pervasive to urban environments and providing the necessary basis for sustainability and resilience of the smart future cities. Often ICT tools for a smart city deal with different application domains e.g. home automation, healthcare, environment monitoring, energy and rarely provide an integrated information perspective to deal with sustainability and socioeconomic growth of the city. Smart cities can benefit from such information using Big data and often real-time cross-thematic, data collection, processing, integration and sharing through inter-operable services deployed in a Cloud environment. However, such information utilisation requires appropriate software tools, services and technologies to collect, store, analyse and visualise large amounts of data from the city environment, citizens and various departments and agencies at city scale.IoT datasets generated by smart healthcare, smart environment, and energy related data sets are used for analysis and evaluation. This framework presents a perspective on the smart cities focused Big data processing and analysis by proposing a Cloud-based analysis service that can be further developed to generate information intelligence and support decision-making in smart cities context.

Problem Statement

Design and development of a framework of smart cities for intelligent processing data analysis.

Smart City is a city which invests in ICT enhanced governance and participatory processes to define appropriate public subscribers’ service and transportation investments, that can ensure sustainable socio-economic development, enhanced quality-of-life and intelligent management of natural resources.Although there is not yet a formal and widely accepted definition of “Smart City,” the final aim is to make a better use of the public resources, increasing the quality of the services offered to the citizens, while reducing the operational costs of the public administrations. This objective can be pursued by the deployment of an urban IoT, i.e., a communication infrastructure that provides unified, simple, and economical access to a plethora of public services, thus unleashing potential synergies and increasing transparency to the citizens.

Building blocks of smart city framework

There are two users who will be benefiting from our smart city framework : general public and the admin who controls the accessibility provided to the general public. The building blocks for smart city framework comprises of -

Internet of Things -

The Internet of things (IoT) is the network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and connectivity which enables these things to connect, collect and exchange data [1], [2] creating opportunities for more direct integration of the physical world into computer-based systems, resulting in efficiency improvements, economic benefits, and reduced human exertions [5] [8].

Big Data -

Big data is a term used to refer to the study and applications of data sets that are so big and complex that traditional data-processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. There are a number of concepts associated with big data: originally there were 3 concepts volume, variety, velocity [6]. Other concepts later attributed with big data are veracity (i.e., how much noise is in the data) [7] and value [19].

Cloud Computing -

Cloud computing is shared pools of configurable computer system resources and higher-level services that can be rapidly provisioned with minimal management effort, often over the Internet.[4] Cloud computing relies on sharing of resources to achieve coherence and economies of scale, similar to a public utility. Third-party clouds enable organizations to focus on their core businesses instead of expending resources on computer infrastructure and maintenance [9]. Some of the commonly used cloud services are Microsoft Azure, Amazon EC2.

Processing and Analysis Engine -

Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making [7]. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, while being used in different business, science, and social science domains.

Machine Learning -

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves [14] [18].

Web Application -

An application running on web platform is a type of application software designed to run on web. These applications frequently serve to provide users with an interactive medium to make requests and get the results.

IoT datasets generated by smart environment, and energy related data sets are used for analysis and evaluation. Big data is defined as high-volume, high-velocity, and high variety data that demands cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation. With respect to the challenges posed by big data, cloud-based analysis services are further developed to generate information intelligence and support decision-making in smart cities context.

The big data is processed and analysed using machine learning algorithms by processing and analysis engine. The results obtained from this engine are processed to respond to the queries of the users and are displayed at the front end which is accessible to the users through mobile application. The mobile application is designed to make the services available to the subscribers according to their requirements through a user friendly and easily understandable interface.

We intend to expand this model to the university campus with an objective of implementing the smart city framework by integrating the data collected from various IOT sensors installed at different parts of the campus with IOT protocols that trigger the commands based on user configuration. To enhance the usability of our smart city framework and to speed up the development of this framework, the APIs of our framework will be implemented using open source technologies.

Issues that can be solved using this framework

IoT sensors that can be used

Machine Learning algorithms that can be used

Web platform design