Green Data Hubs: Monetizing Environmental Monitoring through Open-Access Sensor Networks

Abstract

Long regarded as a mere regulatory obligation, the practice of environmental monitoring is poised on the cusp of a profound economic transformation. In this review, we examine the emergence of "Green Data Hubs," a model in which the deluge of data from open-access sensor networks is not merely gathered, but leveraged. We trace the pathway from low-cost IoT sensor deployment to the generation of tangible value in industries ranging from precision agriculture to sustainable manufacturing, where environmental intelligence is being actively translated into a source of competitive advantage. However, this economic future is not inevitable. Its realization is contingent upon a critical set of prerequisites, ranging from navigating the technical complexity of data standardization, to the often overlooked but essential imperative of establishing public trust and closing the digital divide. Ultimately, we contend that the long-term success of Green Data Hubs hinges on a deliberate, coordinated roadmap that unites policymakers, entrepreneurs, and local industry. By fundamentally redefining environmental data as a foundation of business innovation, these hubs represent a pragmatic pathway to a future wherein economic resilience and ecological sustainability are not competing interests, but deeply intertwined objectives.

References

Abdullah, F., Peng, L., & Tak, B. (2020). Fossel: efficient latency reduction in approximating streaming sensor data. Sustainability, 12(23), 10175.

Alsafery, W., Rana, O., & Perera, C. (2023). Sensing within smart buildings: A survey. ACM Computing Surveys, 55(13s), 1-35.

Anitha, M., & Kumar, L. S. (2023). Development of an IoT-enabled air pollution monitoring and air purifier system. MAPAN, 38(3), 669-688.

Berti-Equille, L., & Raimundo, R. L. (2023). Combining ecological and socio-environmental data and networks to achieve sustainability. Biodiversity Information Science and Standards, 7, e112703.

Divyeshkumar Vaghani. (2024). Leveraging Data Analytics for Environmental Sustainability. The International Journal of Science & Technoledge. https://doi.org/10.24940/theijst/2024/v12/i5/st2405-004

Dou, J., Niemelä, K., Haatainen, T., Tervola, P., & Vehmaa, J. (2023). Investigation of pitch deposits throughout the fiber line of softwood pulp mill. Journal of Cleaner Production, 405, 136940.

Dr Susheelamma K H, Basavaraj S Biradar, Bhavana B, & Deekshitha Ram. (2024). Air and Water Quality Indexing and Environment Monitoring. International Journal of Advanced Research in Science, Communication and Technology, 385–390. https://doi.org/10.48175/ijarsct-18065

Ejibe, I., Nwankwo, T. C., Nwankwo, E. E., Okoye, C. C., & Scholastica, U. C. (2024). Advancing environmental sustainability in the creative sectors: A strategic HR framework based on data analytics and eco-innovation. World Journal of Advanced Research and Reviews, 21(3), 050-060.

Feng, K., & Bao, C. (2024). The Impact of Environmental Management Capabilities on the Economic Value Added of Industrial Enterprises—Empirical Evidence from China. Sustainability, 16(8), 3356.

Hamamcı, S. F., & Doğru, A. Ö. (2024). Low-cost real-time environmental noise monitoring system design and implementation. International Journal of Environmental Studies, 81(3), 1045-1057.

Hundekar, S.P., Hundekar, S.P., Varur, A.S., Shetty, V.C., Shankar, V., & Kulkarni, K. (2024). IOT based noise pollution and water quality monitoring system. International Journal of Science and Research Archive.

Janicka, M., & Sajnóg, A. (2023). Do environmental and economic performance go hand in hand? An industrial analysis of European Union companies with the non‐parametric data envelopment analysis method. Corporate Social Responsibility and Environmental Management, 30(5), 2590-2605.

Koldasbayeva, D., Tregubova, P., Gasanov, M., Zaytsev, A., Petrovskaia, A., & Burnaev, E. (2023). Challenges in data-based geospatial modeling for environmental research and practice. arXiv preprint arXiv:2311.11057.

Li, C., & Huang, M. (2023). Environmental sustainability in the age of big data: opportunities and challenges for business and industry. Environmental Science and Pollution Research, 30(56), 119001-119015.

Lingaraju, A. K., Niranjanamurthy, M., Bose, P., Acharya, B., Gerogiannis, V. C., Kanavos, A., & Manika, S. (2023). IoT-based waste segregation with location tracking and air quality monitoring for smart cities. Smart Cities, 6(3), 1507-1522.

Luoma, P., Rauter, R., Penttinen, E., & Toppinen, A. (2023). The value of data for environmental sustainability as perceived by the customers of a tissue‐paper supplier. Corporate Social Responsibility and Environmental Management, 30(6), 3110-3123.

Masselot, P., Chebana, F., Lavigne, É., Campagna, C., Gosselin, P., & Ouarda, T. B. (2019). Toward an improved air pollution warning system in Quebec. International journal of environmental research and public health, 16(12), 2095.

Mesquita, P., Gong, L., & Lin, Y. (2022). Low-cost microfluidics: Towards affordable environmental monitoring and assessment. Frontiers in Lab on a Chip Technologies, 1, 1074009.

Milutinović, M. (2024). Machine learning in environmental monitoring. Facta Universitatis, Series: Working and Living Environmental Protection, 155-160.

Nalakurthi, N. V. S. R., Abimbola, I., Ahmed, T., Anton, I., Riaz, K., Ibrahim, Q., ... & Gharbia, S. (2024). Challenges and opportunities in calibrating low-cost environmental sensors. Sensors, 24(11), 3650.

Nandagopal, V., Kalaichelvi, S., Kumar, S. S., Manikandaprabhu, K., Srinivasan, S., & Karunakaran, A. (2024, November). Wireless Sensor Networks for Environmental Management in IoT: Air and Water Quality Using Decision Tree Algorithm. In 2024 International Conference on Smart Technologies for Sustainable Development Goals (ICSTSDG) (pp. 1-6). IEEE.

Narayana, T. L., Venkatesh, C., Kiran, A., Kumar, A., Khan, S. B., Almusharraf, A., & Quasim, M. T. (2024). Advances in real time smart monitoring of environmental parameters using IoT and sensors. Heliyon, 10(7).

Okafor, N. U., Alghorani, Y., & Delaney, D. T. (2020). Improving data quality of low-cost IoT sensors in environmental monitoring networks using data fusion and machine learning approach. ICT express, 6(3), 220-228.

Panduman, Y. Y. F., Funabiki, N., Puspitaningayu, P., Kuribayashi, M., Sukaridhoto, S., & Kao, W. C. (2022). Design and implementation of SEMAR IOT server platform with applications. Sensors, 22(17), 6436.

Radha, Mrs. C., Madheswaran, Mr. M., Lokesh, Mr. M., & Althaf, Mr. M. M. (2024). Environmental Monitoring in Internet of Things (IOT). International Journal for Research in Applied Science and Engineering Technology, 12(4), 1658–1663. https://doi.org/10.22214/ijraset.2024.60086

Raghuvanshi, A., Singh, U. K., Sajja, G. S., Pallathadka, H., Asenso, E., Kamal, M., ... & Phasinam, K. (2022). Intrusion detection using machine learning for risk mitigation in IoT‐enabled smart irrigation in smart farming. Journal of Food Quality, 2022(1), 3955514.

Ramadan, Q., Boukhers, Z., AlShaikh, M., Lange, C., & Jurjens, J. (2023, December). Data Trading and Monetization: Challenges and Open Research Directions. In Proceedings of the 7th International Conference on Future Networks and Distributed Systems (pp. 344-351).

Schmitt, T., Bejarano, R., & Assuad, C. (2024). Challenges and opportunities of automated data pipelines for environmental sustainability applications in industrial manufacturing. Procedia CIRP, 122, 623-628.

Sugiharto, W. H., Susanto, H., & Prasetijo, A. B. (2024). Selecting IoT-Enabled Water Quality Index Parameters for Smart Environmental Management. Instrumentation, Mesures, Métrologies, 23(4).

Sun, P., Liu, W., Xu, Y., & Wang, L. (2021, February). Research on application of real-time database for air quality automatic monitoring system. In IOP Conference Series: Earth and Environmental Science (Vol. 675, No. 1, p. 012023). IOP Publishing.

Veiga, T., Munch-Ellingsen, A., Papastergiopoulos, C., Tzovaras, D., Kalamaras, I., Bach, K., ... & Akselsen, S. (2021). From a low-cost air quality sensor network to decision support services: Steps towards data calibration and service development. Sensors, 21(9), 3190.

Wang, B., Klemeš, J. J., Li, N., Zeng, M., Varbanov, P. S., & Liang, Y. (2021). Heat exchanger network retrofit with heat exchanger and material type selection: A review and a novel method. Renewable and Sustainable Energy Reviews, 138, 110479.

Weltman, T. (2024). Smart Tourism Ecosystem Development Readiness in Southeast Asia.

Wolniak, R., & Grebski, W. (2023). ENVIRONMENTAL SUSTAINABILITY–THE BUSINESS ANALYTICS USAGE IN INDUSTRY 4.0 CONDITIONS. Scientific Papers of Silesian University of Technology. Organization & Management/Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie, (187).

Zigui, L., Caluyo, F., Hernandez, R., Sarmiento, J., & Rosales, C. A. (2024). Improving Communication Networks to Transfer Data in Real Time for Environmental Monitoring and Data Collection. Natural and Engineering Sciences, 9(2), 198-212.