The Internet of Nature: How taking nature online can shape urban ecosystems

2019 ◽  
Vol 6 (3) ◽  
pp. 279-287 ◽  
Author(s):  
Nadinè J Galle ◽  
Sophie A Nitoslawski ◽  
Francesco Pilla
Keyword(s):  
Ecosystem Management ◽  
Smart Grids ◽  
Natural Capital ◽  
Smart Cities ◽  
Urban Ecosystems ◽  
Urban Ecosystem ◽  
Natural World ◽  
Ecosystem Dynamics ◽  
The Internet ◽  
Digital Revolution

Many of our cities are going digital. From self-driving cars to smart grids to intelligent traffic signals, these smart cities put data and digital technology to work to drive efficiency and improve the quality of life for citizens. Yet, the natural capital upon which cities rely risks being left behind by the digital revolution. Bringing nature online is the next frontier in ecosystem management and will change our relationship with the natural world in the urban age. In this article, we introduce the ‘Internet of Nature’ to bridge the gap between greener and smarter cities and to explore the future of urban ecosystem management in an age of rapid urbanisation and digitisation. The creation of an Internet of Nature, along with the ecosystem intelligence it provides, is an opportunity to elicit and understand urban ecosystem dynamics, promote self-sufficiency and resilience in ecosystem management and enhance connections between urban social and ecological systems.

scholarly journals Ethics of Smart Cities: Towards Value-Sensitive Design and Co-Evolving City Life

2021 ◽  
Vol 13 (20) ◽  
pp. 11162
Author(s):  
Dirk Helbing ◽  
Farzam Fanitabasi ◽  
Fosca Giannotti ◽  
Regula Hänggli ◽  
Carina I. Hausladen ◽  
...  
Keyword(s):  
Data Privacy ◽  
Smart Cities ◽  
Self Regulation ◽  
Urban Ecosystem ◽  
Global Scale ◽  
Self Control ◽  
Design Approach ◽  
Value Sensitive Design ◽  
Digital Revolution ◽  
Digital World

The digital revolution has brought about many societal changes such as the creation of “smart cities”. The smart city concept has changed the urban ecosystem by embedding digital technologies in the city fabric to enhance the quality of life of its inhabitants. However, it has also led to some pressing issues and challenges related to data, privacy, ethics inclusion, and fairness. While the initial concept of smart cities was largely technology- and data-driven, focused on the automation of traffic, logistics and processes, this concept is currently being replaced by technology-enabled, human-centred solutions. However, this is not the end of the development, as there is now a big trend towards “design for values”. In this paper, we point out how a value-sensitive design approach could promote a more sustainable pathway of cities that better serves people and nature. Such “value-sensitive design” will have to take ethics, law and culture on board. We discuss how organising the digital world in a participatory way, as well as leveraging the concepts of self-organisation, self-regulation, and self-control, would foster synergy effects and thereby help to leverage a sustainable technological revolution on a global scale. Furthermore, a “democracy by design” approach could also promote resilience.

scholarly journals Internet of Things-Based Energy Efficiency Optimization Model in Fog Smart Cities

2021 ◽  
Vol 5 (2) ◽  
pp. 105
Author(s):  
Wasswa Shafik ◽  
S. Mojtaba Matinkhah ◽  
Mamman Nur Sanda ◽  
Fawad Shokoor
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Response Time ◽  
Smart Grids ◽  
Smart Cities ◽  
Fog Computing ◽  
The Internet ◽  
Delay Sensitive ◽  
Service Delay

In recent years, the IoT) Internet of Things (IoT) allows devices to connect to the Internet that has become a promising research area mainly due to the constant emerging of the dynamic improvement of technologies and their associated challenges. In an approach to solve these challenges, fog computing came to play since it closely manages IoT connectivity. Fog-Enabled Smart Cities (IoT-ESC) portrays equitable energy consumption of a 7% reduction from 18.2% renewable energy contribution, which extends resource computation as a great advantage. The initialization of IoT-Enabled Smart Grids including (FESC) like fog nodes in fog computing, reduced workload in Terminal Nodes services (TNs) that are the sensors and actuators of the Internet of Things (IoT) set up. This paper proposes an integrated energy-efficiency model computation about the response time and delays service minimization delay in FESC. The FESC gives an impression of an auspicious computing model for location, time, and delay-sensitive applications supporting vertically -isolated, service delay, sensitive solicitations by providing abundant, ascendable, and scattered figuring stowage and system associativity. We first reviewed the persisting challenges in the proposed state-of-the models and based on them. We introduce a new model to address mainly energy efficiency about response time and the service delays in IoT-ESC. The iFogsim simulated results demonstrated that the proposed model minimized service delay and reduced energy consumption during computation. We employed IoT-ESC to decide autonomously or semi-autonomously whether the computation is to be made on Fog nodes or its transfer to the cloud.

Sampling Sensor Nodes to Extend the Longevity of Wireless Sensor Networks

2019 ◽  
Vol 9 (1) ◽  
pp. 53-63
Author(s):  
Mohammed Baqer ◽  
Luisella Balbis
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Smart Grids ◽  
Smart Cities ◽  
Sampling Rate ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
The Internet ◽  
Detection Accuracy

Background and Objective: Wireless Sensor Networks (WSN) are one of the most important elements in the Internet of Things (IoT) paradigm. It is envisaged that WSNs will seamlessly bridge the physical world with the Internet resulting in countless IoT applications in smart cities, wearable devices, smart grids, smart retails amongst others. It is necessary, however, to consider that sensing, processing and communicating large amounts of sensor data is an energy-demanding tasks. Recharging or replacing those battery-powered sensor nodes deployed in inaccessible locations is generally a tedious and time-consuming task. As a result, energy efficient approaches for WSN need to be devised in order to prolong the longevity of the network. Methods: In this paper, we present an approach that reduces energy consumption by controlling the sampling rate and the number of actively communicating nodes. The proposed approach applies compressive sensing to reduce the sampling rate and a statistical approach to decrease the sample size of sensor nodes. Results and Conclusion: The proposed approach is expected to significantly increase the lifetime of the network whilst maintaining the event detection accuracy.

scholarly journals Toward a Sustainable Cybersecurity Ecosystem

Computers ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 74 ◽  
Author(s):  
Shahrin Sadik ◽  
Mohiuddin Ahmed ◽  
Leslie F. Sikos ◽  
A. K. M. Najmul Islam
Keyword(s):  
Artificial Intelligence ◽  
Smart Grids ◽  
Smart Cities ◽  
Research Community ◽  
The Internet ◽  
Policy Makers ◽  
Associated Solutions ◽  
Emerging Trends ◽  
Learning Frameworks ◽  
The Internet Of Things

Cybersecurity issues constitute a key concern of today’s technology-based economies. Cybersecurity has become a core need for providing a sustainable and safe society to online users in cyberspace. Considering the rapid increase of technological implementations, it has turned into a global necessity in the attempt to adapt security countermeasures, whether direct or indirect, and prevent systems from cyberthreats. Identifying, characterizing, and classifying such threats and their sources is required for a sustainable cyber-ecosystem. This paper focuses on the cybersecurity of smart grids and the emerging trends such as using blockchain in the Internet of Things (IoT). The cybersecurity of emerging technologies such as smart cities is also discussed. In addition, associated solutions based on artificial intelligence and machine learning frameworks to prevent cyber-risks are also discussed. Our review will serve as a reference for policy-makers from the industry, government, and the cybersecurity research community.

IAF: IoT Attack Framework and Unique Taxonomy

2021 ◽  
Author(s):  
Akashdeep Bhardwaj ◽  
Manoj Kumar ◽  
Thompson Stephan ◽  
Achyut Shankar ◽  
Muhammad Rukunuddin Ghalib ◽  
...  
Keyword(s):  
Smart Grids ◽  
Smart Cities ◽  
The Internet ◽  
Cloud Infrastructure ◽  
Service Levels ◽  
Industrial Iot ◽  
Critical Issues ◽  
Communication Devices ◽  
Iot Devices ◽  
The Impact

In the early 2000s, the Internet meant being able to connect different communication devices, whereas the focus in the last few years is on connecting “things” to the Internet. Although there is no distinct classification for these devices and things on the Internet, the Internet of Things (IoT) ecosystem primarily consists of a complex network of devices, sensors, and things. These “things” are controlled by humans and utilize the existing cloud infrastructure. These devices provide facilities and benefits to make our lives comfortable. IoT domains include smart homes, healthcare, manufacturing, smart wearables, smart cities, smart grids, industrial IoT, connected vehicles, and smart retail. Different IoT models involve human-to-IoT, IoT-to-IoT, IoT-to-traditional systems architectures. In most scenarios, the architecture ends up connecting to the unsecured Internet. This has thrown open several critical issues leading to cybersecurity attacks on IoT devices. IoT communications, protocols or the architecture were never been conceptualized to handle the new age cybersecurity attacks. IoT devices have limited compute, storage, network, or memory. In this research, the authors present a unique IoT attack framework named IAF focusing on the impact of IoT attacks on IoT applications and service levels. The authors also proposed an all-inclusive attack taxonomy classifying various attacks on IoT ecosystems.

scholarly journals Application of IoT in Analyzing Cognitive Skills of Students-A Systematic Literature Review

2020 ◽  
pp. 158-184
Author(s):  
Rajeshwari M. ◽  
Krishna Prasad K.
Keyword(s):  
Problem Solving ◽  
Internet Of Things ◽  
Literature Review ◽  
Smart Grids ◽  
Cognitive Skills ◽  
Conceptual Knowledge ◽  
Smart Cities ◽  
The Internet ◽  
Digital World ◽  
The Internet Of Things

The Internet of Things is an interrelated system of computer equipment, digital and mechanical machinery with unique identifiers, capable of transferring and relocating data over the Internet in the absence of human-to-computer involvement or without human-to-human interactions. The entire future of the global technology will swing around the Internet of Things, which is bound to connect a large quantity of SOs- Smart Objects, or articles or entities to transform the physical environment around us to a digital world. The application of IoT involves several domains like smart grids, smart farms, better healthcare, smart cities, smart homes, smart transportation system, smart parking and so on. The problem-solving and conceptual knowledge obtained in school is basically inert for several students. In certain situations, knowledge acquired remains surface bound features of problems, as learned from school classes and textbook presentations. The Cognitive computing process uses the available data to react to changes in order to make the right decisions based on specific learning processes from past experiences. In the case of cognitive apprenticeship process, there is a need to bring deliberately the thinking process and thoughts emerge, to produce them to be visible, whether in the case of writing, reading, or problem solving. The thoughts of the teacher must be completely visible to all the students, while the thinking of students must be clearly visible and readable to the teacher. The mental capabilities of students are developed through the cognitive skills that the students need to learn to be successful in school. To effectively understand, write, read, analyze, remember, think, and solve all the problems, the students of these cognitive skills should gather so as to function collectively and properly. If these skills become weak, the students will start to struggle, unable to face problems and solve them correctly. The new learning method makes the students observe, perform and practice the subjects from both the teachers and their peers. In view of this, this study of literature review investigates and explains the concept of IoT by conducting a systematic review and assessment of corporate and communal white papers, scholarly research articles, journals and papers, professional dialogues and discussions with researchers, academicians, scholars, educational experts along with online database available. Purpose and goal of this paper is to analytically categorize, and examine the prevailing research techniques and applications of IoT approaches on cognitive skills of students towards personalization in education. The limitation of the study is that it deals only with the subject matter's application components which leave physical components.

scholarly journals The Internet of Things for Smart Environments

2020 ◽  
Vol 12 (3) ◽  
pp. 51 ◽  
Author(s):  
Giuseppe Ruggeri ◽  
Valeria Loscrí ◽  
Marica Amadeo ◽  
Carlos T. Calafate
Keyword(s):  
Internet Of Things ◽  
Smart Grids ◽  
Smart Cities ◽  
The Internet ◽  
Smart Environments ◽  
Building Automation ◽  
Smart Objects ◽  
Smart Transportation ◽  
The Internet Of Things

By leveraging the global interconnection of billions of tiny smart objects, the Internet of Things (IoT) paradigm is the main enabler of smart environments, ranging from smart cities to building automation, smart transportation, smart grids, and healthcare [...]

scholarly journals Advances in the Application of Machine Learning Techniques for Power System Analytics: A Survey

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4776
Author(s):  
Seyed Mahdi Miraftabzadeh ◽  
Michela Longo ◽  
Federica Foiadelli ◽  
Marco Pasetti ◽  
Raul Igual
Keyword(s):  
Machine Learning ◽  
Power Systems ◽  
Smart Grids ◽  
State Of The Art ◽  
Smart Cities ◽  
Power Grids ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
New Research ◽  
Traditional Approaches

The recent advances in computing technologies and the increasing availability of large amounts of data in smart grids and smart cities are generating new research opportunities in the application of Machine Learning (ML) for improving the observability and efficiency of modern power grids. However, as the number and diversity of ML techniques increase, questions arise about their performance and applicability, and on the most suitable ML method depending on the specific application. Trying to answer these questions, this manuscript presents a systematic review of the state-of-the-art studies implementing ML techniques in the context of power systems, with a specific focus on the analysis of power flows, power quality, photovoltaic systems, intelligent transportation, and load forecasting. The survey investigates, for each of the selected topics, the most recent and promising ML techniques proposed by the literature, by highlighting their main characteristics and relevant results. The review revealed that, when compared to traditional approaches, ML algorithms can handle massive quantities of data with high dimensionality, by allowing the identification of hidden characteristics of (even) complex systems. In particular, even though very different techniques can be used for each application, hybrid models generally show better performances when compared to single ML-based models.

scholarly journals Internet of Samples (iSamples): Toward an interdisciplinary cyberinfrastructure for material samples

GigaScience ◽  
2021 ◽  
Vol 10 (5) ◽  
Author(s):  
Neil Davies ◽  
John Deck ◽  
Eric C Kansa ◽  
Sarah Whitcher Kansa ◽  
John Kunze ◽  
...  
Keyword(s):  
Best Practices ◽  
Built Environment ◽  
21St Century ◽  
Natural Science ◽  
Natural World ◽  
The Internet ◽  
Data Standards ◽  
Meta Data ◽  
Cross Domain ◽  
Data Stewardship

Abstract Sampling the natural world and built environment underpins much of science, yet systems for managing material samples and associated (meta)data are fragmented across institutional catalogs, practices for identification, and discipline-specific (meta)data standards. The Internet of Samples (iSamples) is a standards-based collaboration to uniquely, consistently, and conveniently identify material samples, record core metadata about them, and link them to other samples, data, and research products. iSamples extends existing resources and best practices in data stewardship to render a cross-domain cyberinfrastructure that enables transdisciplinary research, discovery, and reuse of material samples in 21st century natural science.

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