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Smart Trends of Systems, Security and Sustainability

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (30 September 2019) | Viewed by 10810

Special Issue Editor


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Guest Editor
Department of Engineering, University of Almeria, 04120 Almeria, Spain
Interests: monitoring and sensing across multiple fields of application; measurements of natural phenomena in the ELF band; ambient variables monitoring in tourist caverns; dielectric measurements; biomedical monitoring; agricultural applications; renewable energies
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Special Issue Information

Dear Colleagues,

Intelligent systems enhance information flux inside the system to improve its control. The popularity of these systems is on the rise, invading the whole world in different fields, like energy production, sustainable agriculture, sustainable transport, intelligent building, and intelligent cities. Most of these systems take advantage of information technology to drive innovation and colaborative networking. The digital world helps us to build a sustainable world, trying to balance a thousand social, economic, and environmental factors, among others. Thus, how to employ intelligent systems to drive and improve efficiency, safety and sustainability has become an issue of global importance. Still, many of these systems have issues regarding privacy and safety, causing companies to be reasonably sure that these problems are addressed before releasing a product. This Special Issue will encourage articles of scientific and technologic research into new sustainable trends that expand current frame of knowledge while using intelligent systems. We hereby invite articles that sketch interdisciplinary processes as well as processes where practical and scientific collaboration is required to implement sustainable intelligent systems in different fields.

Any author interested in this field but unsure whether their work is aligned with the goals of this Special Issue are welcome to contact the Guest Editor of this Special Issue.

Appropriate topics include, but are not limited to:

  • Smart trends in sustainable production
  • Smart trends in sustainable development
  • Smart trends in clean energy security
  • Smart trends in the transition of energy systems
  • The transition of energy systems and data privacy and security
  • New sustainable business models
  • Sustainable transport
  • Trends in intelligent cities or intelligent architecture
  • Sustainable security
  • Sustainability of agriculture
  • Sustainable conservation of geological assets
  • Sustainable crop production

References:

  1. Obradović, V.; Todorović, M.; Bushuyev, S. Sustainability and Agility in Project Management: Contradictory or Complementary? Intell. Syst. Comput. 2019, 871, 522–532, doi.10.1007/978-3-030-01069-0_37.
  2. Waheed, M.F.; Khalid, A.M. Impact of emerging technologies for sustainable fashion, textile and design. Intell. Syst. Comput. 2019, 903, 684–689, doi.10.1007/978-3-030-11051-2_104.
  3. Pan, L.; Wu, H. Smart trend-traversal: A low delay and energy tag arbitration protocol for large RFID systems. (2009) In Proceedings of IEEE INFOCOM, Rio de Janeiro, Brazil, 19–25 April 2009; IEEE, 2009; no. 5062189, pp. 2571–2575, doi.10.1109/INFCOM.2009.5062189.
  4. Hannan, M.A.; Azidin, F.A.; Mohamed, A. Hybrid electric vehicles and their challenges: A review. Sustain. Energy Rev. 2014, 29, 135–150. doi.10.1016/j.rser.2013.08.097.
  5. Mocerino, C. Digital revolution in efficient self-organization of buildings: Towards intelligent robotics. (2018) In Proceedings of 2018 Energy and Sustainability for Small Developing Economies (ES2DE), Funchal, Portugal, 9–12 July 2018; IEEE, 2018; art. no. 8494237, pp. 27–32, doi.10.1109/ES2DE.2018.8494237.
  6. Mejia, D.; Villanueva-Rosales, N.; Torres, E.; Cheu, R.L. Integrating heterogeneous freight performance data for smart mobility. (2018) In Proceedings of 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), San Francisco, CA, USA, 4–8 August 2017; IEEE, 2018; pp. 1–8, doi.10.1109/UIC-ATC.2017.8397581.
  7. Yang, R.; Newman, M.W. Learning from a learning thermostat: Lessons for intelligent systems for the home. In Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing, Zurich, Switzerland, 8–12 September, 2013; ACM: New York, NY, USA, 2013; pp. 93–102, doi.10.1145/2493432.2493489.
  8. Piro, G.; Cianci, I.; Grieco, L.A.; Boggia, G.; Camarda, P. Information centric services in Smart Cities. (2014) Syst. Softw. 2014, 88, 169–188, doi.10.1016/j.jss.2013.10.029.
  9. Teixeira, A.; Sou, K.C.; Sandberg, H.; Johansson, K.H. Secure control systems: A quantitative risk management approach. IEEE Control Sys. 2015, 35, 24–45, doi.10.1109/MCS.2014.2364709.
  10. Byun, J., Park, S. Development of a self-adapting intelligent system for building energy saving and context-aware smart services. (2011) IEEE Trans. Consum. Electron. 2011, 57, 90–98, doi.10.1109/TCE.2011.5735486.
  11. Rodríguez, M.D.; Favela, J.; Preciado, A.; Vizcaíno, A. Agent-based ambient intelligence for healthcare. AI Commun. 2005, 18, 201–216.
  12. Ramchurn, S.D.; Vytelingum, P.; Rogers, A.; Jennings, N.R. Putting the 'smarts' into the smart grid: A grand challenge for artificial intelligence. (2012) ACM, 2012, 55, 86–97, doi.10.1145/2133806.2133825.
  13. Cheng, X.; Hu, X.; Yang, L.; Husain, I.; Inoue, K.; Krein, P.; Lefevre, R.; Li, Y.; Nishi, H.; Taiber, J.G.; Wang, F.Y.; Zha, Y.; Gao, W.; Li, Z. Electrified vehicles and the smart grid: The ITS perspective. IEEE Trans. Intell. Transp. Syst. 2014, 15, 1388–1404, doi.10.1109/TITS.2014.2332472.
  14. Rigas, E.S.; Ramchurn, S.D.; Bassiliades, N. Managing Electric Vehicles in the Smart Grid Using Artificial Intelligence: A Survey. IEEE Trans. Intell. Transp. Syst. 2015, 16, 1619–1635, doi. 10.1109/TITS.2014.2376873.
  15. Alam, A.; Besselink, B.; Turri, V.; Martensson, J.; Johansson, K.H. Heavy-duty vehicle platooning for sustainable freight transportation: A cooperative method to enhance safety and efficiency. IEEE Control Sys.Mag. 2015, 35, 34–56, doi.10.1109/MCS.2015.2471046.
  16. Cimmino, A.; Pecorella, T.; Fantacci, R.; Granelli, F.; Rahman, T.F.; Sacchi, C.; Carlini, C.; Harsh, P. The role of small cell technology in future smart city applications. (2014) Emerg. Technol. 2014, 25, 11–20, doi.10.1002/ett.2766.

Dr. Nuria Novas Castellano
Guest Editor

Manuscript Submission Information

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Keywords

  • Sustainable
  • Intelligent systems
  • Indicators of safety and sustainability
  • Smart trends
  • Smart emerging trends
  • Ubiquitous technology
  • Smart power grids
  • Information and communications technology
  • Smart
  • Smart contracts
  • Deep learning
  • Machine learning
  • Legal issues of technology

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Published Papers (2 papers)

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20 pages, 3336 KiB  
Article
Communication Barrier, Spillover Effect and Industrial-Technological Innovation
by Jin Guo, Bingmei Gu, Xialing Sun, Jinli Xue and Baiyun Yuan
Sustainability 2019, 11(18), 4841; https://doi.org/10.3390/su11184841 - 5 Sep 2019
Cited by 3 | Viewed by 2937
Abstract
Industrial-technological innovation (ITI) has far-reaching significance for China’s sustainable development. In this study, we construct an ITI model to analyze the impact of communication barrier and spillover effects in ITI system from the perspective of system by means of system dynamics. Statistical data [...] Read more.
Industrial-technological innovation (ITI) has far-reaching significance for China’s sustainable development. In this study, we construct an ITI model to analyze the impact of communication barrier and spillover effects in ITI system from the perspective of system by means of system dynamics. Statistical data of smartphone industry were collected to verify the authenticity of the model, which show that the model has higher goodness of fit with the real-world. Simulation experiments were carried out and the results showed that: (1) Spillover effects have obvious effects on ITI in both positive and negative radiation directions, and deeper exchanges and cooperation should be encouraged to carry out among firm. (2) Communication barrier play an important role in regulating ITI. Under the condition of non-barrier and complete-barrier, the completion time of the whole process has increased by 76.5%, it is urgent to reduce communication carrier. The research puts forward suggestions to help improve ITI from institutional, market, and government. Full article
(This article belongs to the Special Issue Smart Trends of Systems, Security and Sustainability)
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26 pages, 8614 KiB  
Article
The Blockchain Consensus Algorithm for Viable Management of New and Renewable Energies
by Jun-Ho Huh and Seong-Kyu Kim
Sustainability 2019, 11(11), 3184; https://doi.org/10.3390/su11113184 - 6 Jun 2019
Cited by 50 | Viewed by 7373
Abstract
Efficient information flow in an intelligent system is vital for effectively controlling the entire system. Currently, intelligent systems are used in many industries related to energy production, sustainable agriculture/transport, and intelligent building/cities. Information technology (IT) and information and communication technologies (ICT) play vital [...] Read more.
Efficient information flow in an intelligent system is vital for effectively controlling the entire system. Currently, intelligent systems are used in many industries related to energy production, sustainable agriculture/transport, and intelligent building/cities. Information technology (IT) and information and communication technologies (ICT) play vital roles in introducing technical or technological innovation in these industries as well as establishing a collaborative network. Also, the digitization of existing systems has been quite effective at creating a sustainable global environment as it allows more efficient and well-balanced control of socio-economic factors. However, it has become clear that adopting an intelligent system to achieve innovation, sustainability, and safety may well depend on the quality of the algorithms to be used for that very system. Despite recent controversies, new and renewable energies are considered as a realistic alternative to fossil fuels, which have been integral to modern industries but are regarded as a cause of environmental or economic problems, not to mention their limited deposits. Therefore, since renewable energies will gradually replace existing energy sources but require more time to be fully available, it is essential to find a method of managing them in a fair and transparent way. The United States, Japan, and some European countries are attempting to achieve such a goal by utilizing a blockchain system, but the issues pertaining to its functionality, security, or efficiency have yet to be addressed. This study introduces a viable consensus algorithm (Hyper Delegation Proof of Randomness, or HDPoR algorithm) for blockchain and attempts to validate its parallel computing capability through simulations. This study also attempts to design an efficient but secure peer-to-peer (P2P) transaction service model for these energies for the future where blockchain-based systems will hold a key position in the digitalized world. As its main contribution, this study introduces an effective method of applying blockchain to a new and renewable energy transaction system by presenting a consensus algorithm that can improve its infrastructure and performance. Full article
(This article belongs to the Special Issue Smart Trends of Systems, Security and Sustainability)
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