Computer-Supported Smart Green-Blue Infrastructure Management
DOI:
https://doi.org/10.15837/ijccc.2023.2.5286Keywords:
multi-participant real-time DSS, multi-agent cooperative scheme, Big Data and analytics, mobile and edge computing, IIoT and cobotsAbstract
Answering climate change challenges, the paper proposes an intelligent decision support system (DSS) for the management of green-blue infrastructure (GBI). Addressing the gaps identified in other studies, the designed DSS incorporates four key elements: 1/interdisciplinary collaboration among all stakeholders 2/inclusion of practical operation and maintenance activities, 3/main components of distributed DSS, with practical examples of use, 4/consideration of conditions specific to the location. The multi-layered DSS architecture can be implemented as a unified platform that provides a comprehensive, customizable, and flexible framework based on AI tools, big data and analytics, edge computing, cloud, and mobile, IIoT, and biometric system tools. The use of cobots and digital clones alongside humans results in the implementation of hybrid human-machine units. DSS for GBI increases decision-making capacity and can serve as a foundation for the implementation of similar systems by governments and local communities to build sustainable and resilient communities.References
Aftab, A.;Khan, F.A.; Khan, M.K., Abbas, H.; Iqbal, W; Riaz, F. (2021).Hand-based multibiometric systems: state-of-the-art and future challenges. PeerJ Computer Science 7:e707., 2021.
https://doi.org/10.7717/peerj-cs.707
Alshahadeh, T. (2018). Smart Cities, Smarter Management: developing a Smart framework for smart city projects, Management in Europe, Aydin University, Istanbul, Turkey GE-International Journal of Management Research ISSN (O): (2321-1709), ISSN (P): (2394-4226), Volume 6, Issue 9, September 2018, 2018. Accessed on March 10.03.2023.
Avasalcai, C.; Murturi, I.; Dustdar, S. (2020). Edge and fog: A survey, use cases, and future challenges. Fog Computing: Theory and Practice, Wiley, pp.43-65, 2020.
https://doi.org/10.1002/9781119551713.ch2
Azlah, M.A.F.; Chua, L.S.; Rahmad, F.R.; Abdullah, F.I.; Wan Alwi, S.R. (2019). Review on Techniques for Plant Leaf Classification and Recognition. Computers 2019, 8, 77, 2019.
https://doi.org/10.3390/computers8040077
Brom P., et. all (2023). A Decision Support Tool for Green Infrastructure Planning in the Face of Rapid Urbanization. Land. 2023; 12(2):415. 2023.
https://doi.org/10.3390/land12020415
Candea C., Filip F.G. (2016).Towards Intelligent Collaborative Decision Support Platforms, Studies in Informatics and Control, ISSN 1220-1766, vol. 25(2), pp. 143-152. 2016.
https://doi.org/10.24846/v25i2y201601
Chamoso, P., González-Briones, A., De La Prieta, F., Venyagamoorthy, G.K. and Corchado, J.M. (2020) Smart city as a distributed platform: Toward a system for citizen-oriented management. Computer communications, 152, pp.323-332 (2020). Accessed on March 10.03.2023.
https://doi.org/10.1016/j.comcom.2020.01.059
Choi, C., Berry, P., Smith A. (2021).The climate benefits, co-benefits, and trade-offs of green infrastructure: A systematic literature review. J Environ Manage. 2021 Aug 1;291:112583. 2021.
https://doi.org/10.1016/j.jenvman.2021.112583
[online] Development of the world population from 1950 to 2050 (in billions). Statista 2023, Available: https://www.statista.com/statistics/262875/development-of-the-world-population/, Accessed on March 09.03.2023.
Diop, E.B.; Chenal, J.; Tekouabou, S.C.K.; Azmi, R. (2022). Crowdsourcing Public Engagement for Urban Planning in the Global South: Methods, Challenges and Suggestions for Future Research. Sustainability 2022, 14, 11461.
https://doi.org/10.3390/su141811461
El Zaatari, S., Marei, M., Li, W., Usman, Z. (2019). Cobot programming for collaborative industrial tasks: An overview, Robotics and Autonomous Systems, Volume 116, 2019, Pages 162-180.
https://doi.org/10.1016/j.robot.2019.03.003
[online] European Commission (EC). Communication from the Commission to the European Parliament, The Council, the European Economic and Social Committee and the Committee of the Regions. Green Infrastructure (GI)-Enhancing Europe's Natural Capital. COM(2013) 249 Final, Accessed on March 10.03.2023.
[online] European Commission (EC).The Multifunctionality of Green Infrastructure. Science for Environmental Policy. In-Depth Reports, March 2012, Available: https://ec.europa.eu/environment/nature/ecosystems/docs/Green_Infrastructure.pdf. Accessed on March 10.0
[online] European Commission (EC). Communication from the Commission to the European Parliament, The Council, the European Economic and Social Committee and the Committee of the Regions. Green Infrastructure (GI)-Enhancing Europe's Natural Capital. COM(2013) 249 Final. Accessed on March 10.03.2023.
Fan, X., Wei, H., Zhang, Q., Wang, Y. (2021). Smart decision-making system for green-blue infrastructure planning and management. Environmental Science and Pollution Research, 28(2), 1474-1484, 2021.
Farshidi, S., Jansen, S., de Jong, R., Brinkkemper, S. (2018). A decision support system for software technology selection, Journal of Decision Systems, 27:sup1, 98-110, DOI: 10.1080/12460125.2018.1464821 (Access at A decision support system for software technology selection (tandfonline.com)).
https://doi.org/10.1080/12460125.2018.1464821
Feiran, L., Jianfeng, Z. (2022). A review of the progress in Chinese Sponge City programme: challenges and opportunities for urban stormwater management. Water Supply 1 February 2022
(2): 1638-1651, 2022. 18] Filip, F.G. Collaborative decision-making: concepts and supporting information and communication technology tools and systems. International Journal of Computers Communications and Control 17(2), 2021.
https://doi.org/10.15837/ijccc.2022.2.4732
Filip, F.G., Leiviska, K. (2023). Infrastructure and Complex Systems Automation. In: Nof S Y (ed.) Handbook-of-Automation, 2023. Second edition, Springer, ISBN: 9783030967284. Accessed on March Accessed on March 10.03.2023.
Filip, F.G., Zamfirescu, C.B., Ciurea, C.: (2017). Computer-Supported Collaborative DecisionMaking. Springer, Cham. Accessed on March 10.03.2023.
https://doi.org/10.1007/978-3-319-47221-8
Filip, F.G. (2012).A decision-making perspective for designing and building information systems. Int. J. Comput. Commun. 7(2), 264-272, 2012. Accessed on March 10.03.2023.
https://doi.org/10.15837/ijccc.2012.2.1408
Filip. F.G. (2021). Automation and computers and their contribution to human well-being and resilience. Studies in Informatics and Control 30(4), 5-18, 2021.
https://doi.org/10.24846/v30i4y202101
Frank L., et.al (2016). Cooperative Control of Multi-Agent Systems, ISBN: 1447171942, Springer London Ltd. 2016. Accessed on March 10.03.2023.
[24] Grabowski, Z.J. et al (2022). What is green infrastructure? A study of definitions in US city planning. Frontiers in Ecology and the Environment, 20(3), pp.152-160, 2445, 2022.
https://doi.org/10.1002/fee.2445
Hamann, F., Blecken, G.-T., Ashley, R. M., Viklander, M. (2023). Valuing the Multiple Benefits of Blue-Green Infrastructure for a Swedish Case Study: Contrasting the Economic Assessment Tools B£ST and TEEB. Journal of Sustainable Water in the Built, 2023.
Hassan, R. et. al, (2022). Green Infrastructure: Materials and Applications, Springer Nature Singapore Pte Ltd. 2022. 2022.
Jobin, A., Ienca, M., Vayena, E. (2019).The global landscape of ethics guidelines. AI. Nature Machine Intelligence, 1(9), 389-399), 2019.
https://doi.org/10.1038/s42256-019-0088-2
Kang, D., Yu, J., Choi, J. (2021). Biases in satellite-based vegetation indices and their impacts on machine learning prediction of green infrastructure distribution in urban areas. Landscape and Urban Planning, 213, 103999, 2021.
Kim, D., Song, S.K. (2019) The Multifunctional Benefits of Green Infrastructure in Community Development: An Analytical Review Based on 447 Cases. Sustainability 2019, 11, 3917, 2019. Accessed: https://www.mdpi.com/2071-1050/11/14/3917
https://doi.org/10.3390/su11143917
Li, G., Wu, J., Li, J., Wang, K., Ye, T. (2018). Service Popularity-Based Smart Resources Partitioning for Fog Computing-Enabled Industrial Internet of Things, IEEE Transactions on Industrial Informatics, vol. 14, no. 10, pp. 4702-4711, Oct. 2018, do
https://doi.org/10.1109/TII.2018.2845844
Li, M., Zhang, J., Li, Y., Li, W. (2020). An analysis of the research progress and prospects of urban air quality research based on artificial intelligence. Journal of Cleaner Production, 257, 120553, 2020.
Marjani, M. et al.(2017). Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges, IEEE Access, vol. 5, pp. 5247-5261, doi: 10.1109/ACCESS.2017.2689040 (Access at: https://ieeexplore.ieee.org/document/7888916), 2017.
https://doi.org/10.1109/ACCESS.2017.2689040
O'Donnell, E.C.; Netusil, N.R.; Chan, F.K.S.; Dolman, N.J.; Gosling, S.N. (2021). International Perceptions of Urban Blue-Green Infrastructure: A Comparison across Four Cities. Water 2021, 13, 544, 2021. 34] O'Donnell, E., Woodhouse, R., Thorne, C. (2018). Evaluating the multiple benefits of a Newcastle SuDS scheme. Proc. Inst. Civ. Eng. Water Manag. 2018, 171, 191-2026, 2018. Accessed on March 10.03.2023.
Özbek, N.S. (2020). Co-Design Approach and Co-Simulation Tools for Networked Cyber-Physical Control Systems, November 2020, DOI:10.1109/3ICT51146.2020.9311967, (2020) International Conference on Innovation and Intelligence for Informatics, Computing and Technologies (3ICt), 2020.
https://doi.org/10.1109/3ICT51146.2020.9311967
Palla, A., Pagliaro, G., Lafortezza, R. (2021). Community-based maintenance of green infrastructure: An exploratory study. Journal of Environmental Management, 297, 113338, 2021.
https://doi.org/10.1016/j.jenvman.2021.113338
[online] Percentage of population living in urban areas worldwide from 1950 to 2050, by regional development. Statista 2023, Available: https://www.statista.com/statistics/671366/change-inurbanization-of-countries-worldwide-by-regional, 2023. Accessed on March 10.03.2023.
Rădulescu, C.Z., Rădulescu, I. (2017). An extended TOPSIS approach for ranking cloud service providers. Stud. Inform. Control. 26(2), 183-192, 2017. Accessed on March 10.03.202.
https://doi.org/10.24846/v26i2y201706
Salvia, M., Fernández, M., Paruelo, J. M., Oesterheld, M. (2021). Data-driven decision-making for green infrastructure management in cities. Science of the Total Environment, 751, 141804, 2021.
https://doi.org/10.1016/j.scitotenv.2020.141804
Schrammeijer, E.A., van Zanten, B.T., Verburg, P.H. (2021). Whose park? Crowdsourcing citizen's urban green space preferences to inform needs-based management decisions, Sustainable Cities and Society, Volume 74, 103249, 2021.
https://doi.org/10.1016/j.scs.2021.103249
Schneider, S., Greenberg, S., Taylor, G.W., Kremer, S.C. (2020). Three critical factors affecting automated image species recognition performance for camera traps, 07 March 2020, 2020.
Seidl, R., Tisdell, J. G. (2021).Decision support systems in sustainable water management: a review of current applications and future directions. Sustainability,
Spohrer, J., Maglio, P.P., Vargo, S.L., Varg, M. (2022). Service in the AI Era
Science, Logic, and Architecture Perspective, Business Experts Press LLS, ISBN-13: 978-1-63742-304-2, 2022.
Stoica, I., Shenker, S., (2021).From Cloud Computing to Sky Computing. In Workshop on Hot Topics in Operating Systems (HotOS '21), May 31-June 2, 2021, Ann Arbor, MI, USA. ACM, New York, NY, USA, 7 pages. 2021.
https://doi.org/10.1145/3458336.3465301
Sturiale, L., Scuderi A. (2019).The Role of Green Infrastructures in Urban Planning for Climate Change Adaptation. Climate. 2019; 7(10):119, 2019.
https://doi.org/10.3390/cli7100119
Sun, C., Puig, V., Cembrano, G. (2020). Real-Time Control of Urban Water Cycle under CyberPhysical Systems Framework. Water 2020, 12, 406, 2020.
https://doi.org/10.3390/w12020406
Sun, X., Zhang, Y., Zhang, C. (2021). The potential role of artificial intelligence in green infrastructure planning: Evidence from a case study in Shenzhen, China. Land Use Policy, 108, 105459, 2021.
Van Oijstaeijen, W., Van Passel, S, Cools,J. (2020). Urban green infrastructure: A review on valuation toolkits from an urban planning perspective, Journal of Environmental Management, Volume 267,2020,110603, 2020.
https://doi.org/10.1016/j.jenvman.2020.110603
Venkataramanan, V., Lopez, D., McCuskey, D.J., Kiefus, D., McDonald, R.I., Miller, W.M., Packman, A.I., Young, S.R. (2020). Knowledge, attitudes, intentions, and behaviour related to green infrastructure for flood management: A systematic literature review, Science of The Total Environment, Volume 720, 137606, 2020.
https://doi.org/10.1016/j.scitotenv.2020.137606
Visan, M. (2019). Spatial and territorial development planning: digital challenge and reinvention using a multi-disciplinary approach to support collaborative work, 7th International Conference on Information Technology and Quantitative Management (ITQM 2019), Procedia Computer Science, 162, 795-802, 2019. Accessed on March 10.03.2023.
https://doi.org/10.1016/j.procs.2019.12.052
Wang, Y., Gao, S., Li, N., Yu, S. (2021). Crowdsourcing the perceived urban built environment via social media: The case of underutilized land, Advanced Engineering Informatics, Volume 50,2021,101371, ISSN 1474-0346, 2021.
https://doi.org/10.1016/j.aei.2021.101371
Wilbers, G.J., de Bruin, K., Seifert-Dähnn, I., Lekkerkerk, W., Li, H., Budding-Polo Ballinas, M. (2022). Investing in Urban Blue-Green Infrastructure-Assessing the Costs and Benefits of Stormwater Management in a Peri-Urban Catchment in Oslo, Norway. Sustainability 2022, 14, 1934, 2022. Accessed: https://www.mdpi.com/2071-1050/14/3/1934.
https://doi.org/10.3390/su14031934
Xu, C. et. al. (2021). Environmental and economic benefit comparison between coupled greygreen infrastructure system and traditional grey one through a life cycle perspective, Resources, Conservation and Recycling. vol. 174, p.105804, 2021.
https://doi.org/10.1016/j.resconrec.2021.105804
Zhang, K., Yang, Z., Başar, T. (2021). Decentralized multi-agent reinforcement learning with networked agents: recent advances. Front Inform Technol Electron Eng 22, 802-814, 2021.
Additional Files
Published
Issue
Section
License
Copyright (c) 2023 Maria M. Visan, Firicel Mone
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
ONLINE OPEN ACCES: Acces to full text of each article and each issue are allowed for free in respect of Attribution-NonCommercial 4.0 International (CC BY-NC 4.0.
You are free to:
-Share: copy and redistribute the material in any medium or format;
-Adapt: remix, transform, and build upon the material.
The licensor cannot revoke these freedoms as long as you follow the license terms.
DISCLAIMER: The author(s) of each article appearing in International Journal of Computers Communications & Control is/are solely responsible for the content thereof; the publication of an article shall not constitute or be deemed to constitute any representation by the Editors or Agora University Press that the data presented therein are original, correct or sufficient to support the conclusions reached or that the experiment design or methodology is adequate.
