Abstract
Environment protection is the current need of the hour. The upcoming issues like global warming, air pollution and water pollution are due to the degradation of environment. Measures should be taken to save the nature from further degradation and retrieve back the lost wealth of the nature. This chapter provides insight on methods and approaches to protect the environment. IoT based architecture has been proposed to habituate the environment protection.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ali, S. A., & Affan, M. et al. (2019). A study on efficient energy management techniques for cloud computing environment. 2019 9th International conference on Cloud computing, Data Science & Engineering (Conferences) (pp 13–18)
Al-Masri, E., et al. (2018). Recycle. io: An IoT-enabled framework for urban waste management. In 2018 IEEE International Conference on Big Data (Big Data). IEEE.
Alsouda, Y., Pllana, S., & Kurti, A. (2018). A machine learning driven IoT solution for noise classification in smart cities. In Machine learning driven technologies and architectures for intelligent Internet of Things (ML-IoT). Euromicro.
Andersson, P., Whitehouse, P., et al. (2009). Protection of the environment from ionizing radiation in a regulatory context (protect): Proposed numerical benchmark values. Journal of Environmental Radioactivity, 100(12), 1100–1108.
Chakraborty, T., et al. (2018). Fall-curve: A novel primitive for IoT fault detection and isolation. In Proceedings of the 16th ACM conference on embedded networked sensor systems (pp. 95–107).
Chattha, N. A. (2014). NFC – Vulnerabilities and defense, Conference on Information Assurance and Cyber Security (CIACS) (Vol. 1, pp. 35–38).
Cieplak, T., Rymarczyk, T., & Tomaszewski, R. (2019). A concept of the air quality monitoring system in the city of Lublin with machine learning methods to detect data outliers. In MATEC web of conferences (Vol. 252). EDP Sciences.
Eswaran, S. P., et al. (2014). Event driven opportunistic communication enabler for smart city. In 2014 Eighth International conference on Next Generation Mobile Apps, Services and Technologies, Oxford (pp. 313–319).
Eswaran, S. P., et al. (2015). Service driven dynamic hashing based radio resource management for intelligent transport systems. In Communication technologies for vehicle, Nets4Cars 2015 (Lecture notes in Computer Science) (Vol. 9066). Cham: Springer.
Garcia-Alfaro, J., Herrera-JoancomartÃ, J., & Melià -SeguÃ, J. (2015). Security and privacy concerns about the RFID layer of EPC Gen2 networks. In G. Navarro-Arribas & V. Torra (Eds.), Advanced research in data privacy (pp. 303–324). Springer.
Gómez, J. A., et al. (2017). A case study on monitoring and geolocation of noise in urban environments using the internet of things. In Proceedings of the Second International Conference on Internet of things, Data and Cloud Computing. ACM.
Hamilton, C., et al. (2018). Environmental protection and ecology. In Encyclopedia of ecology (2nd ed.). Elsevier Inc.
Kauder, et al. (2017). Behavioural determinants of proclaimed support for environment protection policies. European Journal of Political Economy.
Mazanik, A. (2018). Industrial waste, river pollution and water politics in Central Russia, 1880–1917. Water History, 10(2–3), 207–222.
McColl, S. T. (2015). Landslide causes and triggers. In Landslide hazards, risks and disasters (pp. 17–42). Academic.
Mihindukulasooriya, N., et al. (2016). FarolApp: Live linked data on light pollution. International Semantic Web Conference (Posters & Demos).
Pan, P., et al. (2018). An intelligent garbage bin based on NB-IOT research mode. In 2018 IEEE International Conference of Safety Produce Informatization (IICSPI). IEEE.
Sadikin, M. F., & Kyas, M. (2014). RFID-Tate: Efficient security and privacy protection. In 5th international conference on information, intelligence, systems and applications (pp. 335–340). IISA.
Sharma, A. B., Golubchik, L., & Ramesh, G. (2010). Sensor faults: Detection methods and prevalence in real-world datasets. ACM Transactions on Sensor Networks (TOSN), 6(3), 23.
Tran, C. T., & Nguyen, P. Q. P. (2019). Some main causes of marine pollution in Vietnam. European Journal of Engineering Research and Science, 4(3), 170–175.
Vambol, S., et al. (2019). The nature and detection of unauthorized waste dump sites using remote sensing. Ecological Questions, 30(3), 1–17.
Worku, Y., & Giweta, M. (2018). Can we imagine pollution free rivers around Addis Ababa city, Ethiopia. What Were the Wrong-Doings, 2.
Zamorano, J., et al. (2019). Night sky brightness monitoring in Spain. Highlights on Spanish Astrophysics X, Proceedings of the XIII Scientific Meeting of the Spanish Astronomical Society held on July 16–20, 2018, in Salamanca, Spain (pp. 599–604).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Eswaran, S.P. (2020). Intelligent Environment Protection. In: Alam, M., Shakil, K., Khan, S. (eds) Internet of Things (IoT). Springer, Cham. https://doi.org/10.1007/978-3-030-37468-6_18
Download citation
DOI: https://doi.org/10.1007/978-3-030-37468-6_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-37467-9
Online ISBN: 978-3-030-37468-6
eBook Packages: Computer ScienceComputer Science (R0)