Analyzing Role of Big Data and IoT in Smart Cities

Big data and Internet of Things (IoT) technologies have evolved and expanded tremendously and hence play a major role in building feasible initiatives for smart city development. IoT and big data form a perfect blend in bringing an interesting and novel challenge to attain futuristic smart cities. These new challenges mainly focus on business and technology related issues that help smart cities to formulate their principles, vision, requirements of smart city applications. In this paper, the role of big data and IoT technologies with respect to smart cities is analyzed. The benefits that smart cities will have from big data and IoT are also discussed. Various challenges faced by smart cities in general related to big data and IoT have also been described here. Moreover, the future statistics of IoT and big data with respect to smart cities is also deliberated

A Study of Components and Benefits of Organic Waste using Decision Tree: A Classifier in Data Mining

Population in India has been growing at a rapid rate. With this increase, there has also been an increase in the amount of wastes being produced especially in the urban cities. Increase in population has led to increase in waste material. Sources of waste are various, generated from industries, agriculture and domestic, but waste management’s schemes are few and improper. Domestic waste is the one generated in huge amount. There are waste management scheme being used by government and non – government organization to properly dispose and manage waste. Due to increase in habitat in various geographic areas and due to mismanagement of people living in a particular geographic area- people throw waste material anywhere they wish in and around they live. This effect the environment like surface water gets contaminated, soil gets contaminated, pollution increases, leachate occurs,etc. all these creates adverse effect on the human being and ecosystem. This paper gives a brief study of the components organic waste and its benefits on human begins and ecosystem by using decision tree classifier of datamining

Automated Evaluation of Smart City Data from Cloud-System

Smart city data processing is an important taskfor the promotion and development of smart cities. The articledescribes and presents the types of smart city data, discusses theexisting modern methods and approaches to the processing ofsmart city data, such as pre-processing, assessment and analysis,and their tasks. This article contains architectural solutions andmethods used in the developed automated smart city dataevaluation system. There is also a detailed description of theintegration of the developed system with the DriveCloud cloudserver for receiving and storing smart city data

Big Data and Its Applications

In times when everything is online, one thing which is common in every application is the use of data. Data is being generated every second, when applications are generating exponentially larger data sets every second it’s the big data which comes into effect. The major objective of this paper is to state the meaning of big data, figure out various ways as how to digest this data. Further this paper will also focus on the applications of Big Data in multiple segments: Finance, Banking and Securities and  Health Care Sector

Work program of the course Digital Communications Technology and Management

Мета та завдання навчальної дисципліни Мета: формування знань про цифрові технології комунікацій та управління, а саме застосування технологій Big Data та Data Mining для аналізу та обробки великих інформаційних масивів в управлінні та комунікаціях, використання Open Data в публічному управлінні. Завдання: вивчення перспектив розвитку комунікацій та управління з використанням новітніх цифрових технологій. Інтегральні компетентності Здатність особи розв’язувати складні задачі і проблеми у певній галузі професійної діяльності або у процесі навчання, що передбачає проведення досліджень та/або здійснення інновацій та характеризується невизначеністю умов і вимог.Цель и задачи учебной дисциплины Цель: формирование знаний о цифровых технологиях коммуникаций и управления, а именно применение технологий Big Data и Data Mining для анализа и обработки больших информационных массивов в управлении и коммуникациях, использование Open Data в публичном управлении. Задача: изучение перспектив развития коммуникаций и управления с использованием новейших цифровых технологий. интегральные компетентности Способность лица решать сложные задачи и проблемы в определенной области профессиональной деятельности или в процессе обучения, предусматривает проведение исследований и / или осуществления инноваций и характеризуется неопределенностью условий и требований.Purpose and objectives of the discipline Objective: To develop knowledge of digital communications and management technologies, namely the use of Big Data and Data Mining technologies to analyze and process large information arrays in management and communications, and to use Open Data in public administration. Objective: To study the perspectives of communication development and management using the latest digital technologies. Integral competencies The ability of a person to solve complex problems and problems in a particular area of ​​professional activity or in a learning process that involves research and / or innovation and is characterized by uncertain conditions and requirements

Single-Board-Computer Clusters for Cloudlet Computing in Internet of Things

The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads, such as low latency, high throughput and bandwidth constraints. Edge computing is becoming the standard computing paradigm for latency-sensitive real-time IoT workloads, since it addresses the aforementioned limitations related to centralised cloud-computing models. Such a paradigm relies on bringing computation close to the source of data, which presents serious operational challenges for large-scale cloud-computing providers. In this work, we present an architecture composed of low-cost Single-Board-Computer clusters near to data sources, and centralised cloud-computing data centres. The proposed cost-efficient model may be employed as an alternative to fog computing to meet real-time IoT workload requirements while keeping scalability. We include an extensive empirical analysis to assess the suitability of single-board-computer clusters as cost-effective edge-computing micro data centres. Additionally, we compare the proposed architecture with traditional cloudlet and cloud architectures, and evaluate them through extensive simulation. We finally show that acquisition costs can be drastically reduced while keeping performance levels in data-intensive IoT use cases.Ministerio de Economía y Competitividad TIN2017-82113-C2-1-RMinisterio de Economía y Competitividad RTI2018-098062-A-I00European Union’s Horizon 2020 No. 754489Science Foundation Ireland grant 13/RC/209