Applications of Artificial Intelligence for Smart Agriculture

2021 ◽  
pp. 277-288
Author(s):  
Suresh Sankaranarayanan
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Smart City ◽  
Autonomous Robots ◽  
Smart Cities ◽  
Building Blocks ◽  
City Management ◽  
Latency Reduction ◽  
Smart Agriculture ◽  
Growing Population

Smart cities is the latest buzzword towards bringing innovation, technology, and intelligence for meeting the demand of ever-growing population. Technologies like internet of things (IoT), artificial intelligence (AI), edge computing, big data, wireless communication are the main building blocks for smart city project initiatives. Now with the upcoming of latest technologies like IoT-enabled sensors, drones, and autonomous robots, they have their application in agriculture along with AI towards smart agriculture. In addition to traditional farming called outdoor farming, a lot of insights have gone with the advent of IoT technologies and artificial intelligence in indoor farming like hydroponics, aeroponics. Now along with IoT, artificial intelligence, big data, and analytics for smart city management towards smart agriculture, there is big trend towards fog/edge, which extends the cloud computing towards bandwidth, latency reduction. This chapter focuses on artificial intelligence in IoT-edge for smart agriculture.

scholarly journals Artificial Intelligence Applications to Smart City and Smart Enterprise

2020 ◽  
Vol 10 (8) ◽  
pp. 2944 ◽  
Author(s):  
Donato Impedovo ◽  
Giuseppe Pirlo
Keyword(s):  
Artificial Intelligence ◽  
Smart City ◽  
Business Models ◽  
Smart Cities ◽  
Wide Spectrum ◽  
Life Quality ◽  
City Management ◽  
Efficient Management ◽  
Social Big Data ◽  
Areas Of Interest

Smart cities work under a more resource-efficient management and economy than ordinary cities. As such, advanced business models have emerged around smart cities, which have led to the creation of smart enterprises and organizations that depend on advanced technologies. In this Special Issue, 21 selected and peer-reviewed articles contributed in the wide spectrum of artificial intelligence applications to smart cities. Published works refer to the following areas of interest: vehicular traffic prediction; social big data analysis; smart city management; driving and routing; localization; and safety, health, and life quality.

RESEARCH ON THE CONSTRUCTION OF A NEW SMART CITY IN HUZHOU (CHINA)

2021 ◽  
pp. 25-29
Author(s):  
Menglin Xu
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Smart City ◽  
New Technologies ◽  
Living Environment ◽  
Scientific Management ◽  
City Management ◽  
Starting Point ◽  
Wide Range ◽  
Countermeasures And Suggestions

Taking solving urban problems and serving urban development as the starting point, smart city comprehensively uses information technology means such as big data, network communication, artificial intelligence and satellite remote sensing to solve population, resource and environmental problems in combination with scientific management methods. It is a new intelligent city model proposed to promote urban health, safety and sustainable development. Through the background of smart city, focusing on the core issues such as what is a smart city, what kind of smart city to build and how to build a smart city, and based on the analysis and investigation of the development status of the smart city in Huzhou, this paper analyzes and expounds the problems existing in the construction of the smart city in Huzhou, This paper puts forward the countermeasures and suggestions to promote the development of the new smart city in Huzhou City. It gives information on further development within the proper implementation of the smart city concept. Firstly, this concept needs a wide range of specialists in the field of management, informatics, geography, architecture, regional economy, who should work in close cooperation synergistically. Secondly, it is substantial to applicate new technologies, for instance, they can be cloud computing, big data, GIS, the Internet of Things and artificial intelligence, etc. The current state of construction of a smart city is emphasized in unsatisfactory condition, hence, the development of the smart city in Huzhou needs all of the above factors. In the light of all evidence, to further develop a smart city, a set of measures is recommended, including clarifying development goals and providing scientific assistance to construction, providing smart planning, strengthening leadership and introduction of new technologies, establishing communications to explain the concept of building a smart city. Such a city will have convenient public services, improved city management, a proper living environment, well-developed intellectual infrastructure and long-term network security.

scholarly journals Smart Cities, Big Data, Artificial Intelligence and Respect for the European Union Data Protection Rules

2020 ◽  
Vol 3 (2) ◽  
pp. 101
Author(s):  
Francisco Javier Durán Ruiz
Keyword(s):  
Artificial Intelligence ◽  
European Union ◽  
Big Data ◽  
Data Protection ◽  
Smart City ◽  
Smart Cities ◽  
Open Data ◽  
Personal Data ◽  
Point Of View ◽  
The European Union

The importance of cities and their populations grow more and more, as well as the need to apply ICT in their management to reduce their environmental impact and improve the services they offer to their citizens. Hence the concept of smart city arises, a transformation of urban spaces that the European Union is strongly promoting which is largely based on the use of data and its treatment using Big data and Artificial Intelligence techniques based in algorithms. For the development of smart cities it is basic, from a legal point of view, EU rules about open data and the reuse of data and the reconciliation of the massive processing of citizens' data with the right to privacy, non-discrimination and protection of personal data. The use of Big data and AI needed for the development of smart city projects requires a particular respect to data protection regulations. In this sense, the research explores in depth the specific hazards of vulnerating this fundamental right in the framework of smart cities due to the use of Big Data and AI.

scholarly journals Big Data in Smart City: Management Challenges

2021 ◽  
Vol 11 (10) ◽  
pp. 4557
Author(s):  
Mladen Amović ◽  
Miro Govedarica ◽  
Aleksandra Radulović ◽  
Ivana Janković
Keyword(s):  
Big Data ◽  
Smart City ◽  
Urban Areas ◽  
Management System ◽  
Smart Cities ◽  
Open Data ◽  
Apache Spark ◽  
City Management ◽  
Real Time System ◽  
Data Framework

Smart cities use digital technologies such as cloud computing, Internet of Things, or open data in order to overcome limitations of traditional representation and exchange of geospatial data. This concept ensures a significant increase in the use of data to establish new services that contribute to better sustainable development and monitoring of all phenomena that occur in urban areas. The use of the modern geoinformation technologies, such as sensors for collecting different geospatial and related data, requires adequate storage options for further data analysis. In this paper, we suggest the biG dAta sMart cIty maNagEment SyStem (GAMINESS) that is based on the Apache Spark big data framework. The model of the GAMINESS management system is based on the principles of the big data modeling, which differs greatly from standard databases. This approach provides the ability to store and manage huge amounts of structured, semi-structured, and unstructured data in real time. System performance is increasing to a higher level by using the process parallelization explained through the five V principles of the big data paradigm. The existing solutions based on the five V principles are focused only on the data visualization, not the data themselves. Such solutions are often limited by different storage mechanisms and by the ability to perform complex analyses on large amounts of data with expected performance. The GAMINESS management system overcomes these disadvantages by conversion of smart city data to a big data structure without limitations related to data formats or use standards. The suggested model contains two components: a geospatial component and a sensor component that are based on the CityGML and the SensorThings standards. The developed model has the ability to exchange data regardless of the used standard or the data format into proposed Apache Spark data framework schema. The verification of the proposed model is done within the case study for the part of the city of Novi Sad.

YOUTH EXPECTATIONS OF SMART CITY LIVING: AN IMPORTANCE- PERFORMANCE ANALYSIS OF YOUNG RESIDENTS’ PERSPECTIVES OF CITY GOVERNMENT

2017 ◽  
Vol 14 (1) ◽  
pp. 118-128
Author(s):  
Jason Cohen ◽  
Judy Backhouse ◽  
Omar Ally
Keyword(s):  
Performance Analysis ◽  
Young People ◽  
Smart City ◽  
Smart Cities ◽  
City Government ◽  
Diagnostic Tools ◽  
City Management ◽  
Bottom Up ◽  
Starting Point ◽  
The City

Young people are important to cities, bringing skills and energy and contributing to economic activity. New technologies have led to the idea of a smart city as a framework for city management. Smart cities are developed from the top-down through government programmes, but also from the bottom-up by residents as technologies facilitate participation in developing new forms of city services. Young people are uniquely positioned to contribute to bottom-up smart city projects. Few diagnostic tools exist to guide city authorities on how to prioritise city service provision. A starting point is to understand how the youth value city services. This study surveys young people in Braamfontein, Johannesburg, and conducts an importance-performance analysis to identify which city services are well regarded and where the city should focus efforts and resources. The results show that Smart city initiatives that would most increase the satisfaction of youths in Braamfontein  include wireless connectivity, tools to track public transport  and  information  on city events. These  results  identify  city services that are valued by young people, highlighting services that young people could participate in providing. The importance-performance analysis can assist the city to direct effort and scarce resources effectively.

scholarly journals Improving Sustainability of Smart Cities through Visualization Techniques for Big Data from IoT Devices

2020 ◽  
Vol 12 (14) ◽  
pp. 5595 ◽  
Author(s):  
Ana Lavalle ◽  
Miguel A. Teruel ◽  
Alejandro Maté ◽  
Juan Trujillo
Keyword(s):  
Big Data ◽  
Smart City ◽  
Smart Cities ◽  
Fire Department ◽  
Heterogeneous Data ◽  
Fire Extinguishing ◽  
Heterogeneous Data Sources ◽  
Iot Devices ◽  
Visualization Techniques ◽  
The Impact

Fostering sustainability is paramount for Smart Cities development. Lately, Smart Cities are benefiting from the rising of Big Data coming from IoT devices, leading to improvements on monitoring and prevention. However, monitoring and prevention processes require visualization techniques as a key component. Indeed, in order to prevent possible hazards (such as fires, leaks, etc.) and optimize their resources, Smart Cities require adequate visualizations that provide insights to decision makers. Nevertheless, visualization of Big Data has always been a challenging issue, especially when such data are originated in real-time. This problem becomes even bigger in Smart City environments since we have to deal with many different groups of users and multiple heterogeneous data sources. Without a proper visualization methodology, complex dashboards including data from different nature are difficult to understand. In order to tackle this issue, we propose a methodology based on visualization techniques for Big Data, aimed at improving the evidence-gathering process by assisting users in the decision making in the context of Smart Cities. Moreover, in order to assess the impact of our proposal, a case study based on service calls for a fire department is presented. In this sense, our findings will be applied to data coming from citizen calls. Thus, the results of this work will contribute to the optimization of resources, namely fire extinguishing battalions, helping to improve their effectiveness and, as a result, the sustainability of a Smart City, operating better with less resources. Finally, in order to evaluate the impact of our proposal, we have performed an experiment, with non-expert users in data visualization.

REGULATION IN MANAGEMENT OF HIGH-TECH INDUSTRIES

2021 ◽  
Vol 2 (65) ◽  
pp. 51-57
Author(s):  
Natalya L. Gagulina ◽  
Keyword(s):  
Artificial Intelligence ◽  
Smart City ◽  
Smart Cities ◽  
Integrated Approach ◽  
High Tech ◽  
Economic Relations ◽  
Regulatory Barriers ◽  
Regulatory Functions ◽  
And Robotics ◽  
Market Disequilibrium

The article analyzes the institutional provision of the regulatory functions of the state in such areas as artificial intelligence and robotics. The analysis is based on the Concept of the development of regulation of relations in the field of artificial intelligence and robotics technologies until 2024. Among the problematic areas of regulation are the restriction of competition, the loss of flexibility in economic relations and the market disequilibrium. It is shown that the solution of these problems requires an integrated approach. So, to implement the concept of “smart city”, it is necessary not only to weaken or remove regulatory barriers, but also to use additional tools that have already applied in the world practice. An opportunity of applying of theoretical and methodological base of quality economics is considered. The solution to a significant part of the problems of digitalization of the region’s economy is the use in the management of the development of the “smart city” the international standard “Sustainable cities and Communities – Indicators for smart cities”.

Using a distributed deep learning algorithm for analyzing big data in smart cities

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammed Anouar Naoui ◽  
Brahim Lejdel ◽  
Mouloud Ayad ◽  
Abdelfattah Amamra ◽  
Okba kazar
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Data Analysis ◽  
Data Storage ◽  
Smart City ◽  
Smart Cities ◽  
Smart Environment ◽  
Data Systems ◽  
Content Type ◽  
Big Data Systems

PurposeThe purpose of this paper is to propose a distributed deep learning architecture for smart cities in big data systems.Design/methodology/approachWe have proposed an architectural multilayer to describe the distributed deep learning for smart cities in big data systems. The components of our system are Smart city layer, big data layer, and deep learning layer. The Smart city layer responsible for the question of Smart city components, its Internet of things, sensors and effectors, and its integration in the system, big data layer concerns data characteristics 10, and its distribution over the system. The deep learning layer is the model of our system. It is responsible for data analysis.FindingsWe apply our proposed architecture in a Smart environment and Smart energy. 10; In a Smart environment, we study the Toluene forecasting in Madrid Smart city. For Smart energy, we study wind energy foresting in Australia. Our proposed architecture can reduce the time of execution and improve the deep learning model, such as Long Term Short Memory10;.Research limitations/implicationsThis research needs the application of other deep learning models, such as convolution neuronal network and autoencoder.Practical implicationsFindings of the research will be helpful in Smart city architecture. It can provide a clear view into a Smart city, data storage, and data analysis. The 10; Toluene forecasting in a Smart environment can help the decision-maker to ensure environmental safety. The Smart energy of our proposed model can give a clear prediction of power generation.Originality/valueThe findings of this study are expected to contribute valuable information to decision-makers for a better understanding of the key to Smart city architecture. Its relation with data storage, processing, and data analysis.

scholarly journals Artificial Intelligence Sebagai Penggerak Industri 4.0 dan Tantangannya Bagi Sektor Pemerintah dan Swasta

2019 ◽  
Vol 10 (1) ◽  
pp. 68
Author(s):  
Reza Yogaswara
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Big Data ◽  
Deep Learning ◽  
Internet Of Things ◽  
Competitive Advantage ◽  
Smart City ◽  
Chief Information Officer ◽  
Deep Learning Neural Network

Artificial Intelligence (AI) atau kecerdasan buatan menjadi penggerak revolusi industri 4.0 yang menjanjikan banyak kemudahan bagi sektor pemerintah maupun industri. Internet of Things (IoT) dan big data contohnya dimana AI dapat diimplementasikan, teknologi yang telah banyak diadopsi di era industri 4.0 ini mampu menghubungkan setiap perangkat, seseorang dapat mengotomatisasi semua perangkat tanpa harus berada di lokasi, lebih dari itu, saat ini telah banyak mesin yang dapat menginterprestasi suatu kondisi atau kejadian tertentu dengan bantuan AI, sebagaimana telah kamera cerdas pendeteksi kepadatan volume kendaraan di jalan raya menggunakan teknologi Deep Learning Neural Network, yang telah diimplementasikan pada beberapa Pemerintah Daerah Kabupaten dan Kota dalam mendukung program Smart City yang telah dicanangkan. Pada sektor industri, banyak juga dari mereka yang telah mengotomatisasi mesin produksi dan manufaktur menggunakan robot dan Artificial Intelligence, sehingga Industri 4.0 akan meningkatkan daya saing melalui perangkat cerdas, setiap entitas yang mampu menguasai teknologi ini disitulah keunggulan kompetitifnya (competitive advantage). Namun ditengah perkembangan industri 4.0 yang cukup masif pemerintah harus bergerak cepat dalam mengadopsi platform ini, jika tidak, mereka akan menurunkan efisiensi proses bisnis untuk menjaga stabilitas layanan publik. Oleh sebab itu diperlukan keilmuan dan pemahaman yang benar bagi pemerintah dalam menghadapai era Industri 4.0, dimana Chief Information Officer (CIO) dapat mengambil peranan penting dalam memberikan dukungan yang didasari atas keilmuan mereka terkait tren teknologi industri 4.0, khususnya AI yang telah banyak diadopsi di berbagai sektor.

Introduction to Smart City and Agricultural Revolution

2019 ◽  
pp. 135-176
Author(s):  
Rajesh Angadi
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Smart City ◽  
Agricultural Development ◽  
Agricultural Revolution ◽  
Information And Communication ◽  
Development Goals ◽  
Smart Agriculture ◽  
National Food Security

In this chapter, a discussion is presented about what Big Data and Internet of Things (IoT) really is and what intricacies are used while building big data and internet of things. Further Big Data and Internet of Things have been used for building an application used for Smart City & Agriculture. A smart city is an urban development vision to integrate multiple information and communication technology (ICT) solutions. Smart city's goal is to improve quality of life with technology to improve the efficiency of services and meet residents' needs. Smart agriculture approach is to develop, transform and reorient agricultural development under new realities of climate change. It increases productivity enhances resilience (adaptation), reduces mitigation with achievement of national food security and development goals. This chapter includes detailed discussion on Smart City and Smart Agriculture along with planning, designing as well as various approaches used to build and implement them effectively.

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