Abstract
The aim of the paper is to investigate the application domain of the Internet of Things (IoT) for efficient and sustained Green Computing (GC). The essence of this research attributes to many IoT and GC issues that need to be addressed in the creation and maintenance of smart society. A lack of strict adherence to these factors may hamper the very application domain of IoT and threatens their environmental sustainability. An effort is made to segment the entire application domain of IoT-based GC (IoTGC) into five relevant categories for better understanding and clarity. These segments are based on factors such as hardware, software, policy, awareness, and recycling. Detail investigations have been made on these segments to highlight the potential issues that may benefit future researchers in this field.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zhu C, Leung VC, Shu L, Ngai EC (2015) Green internet of things for the smart world. IEEE Access 3:2151–2162
Visalakshi P, Paul S, Mandal M (2013) Green computing. Int J Mod Eng Res. In: Proceedings of the national conference on architecture, software systems and green computing (NCASG), pp 63–69
Nandyala CS, Kim HK (2016) Green IoT agriculture and healthcare application (GAHA). Int J Smart Home 10(4):289–300
Kallam S, Madda RB, Chen CY, Patan R, Cheelu D (2017) Low energy-aware communication process in IoT using the green computing approach. IET Netw 1–7
Mekala MS, Viswanathan P (2018) A survey: energy-efficient sensor and VM selection approach in green computing for X-IoT applications. Int J Comput Appl 1–6.
Kamilaris A, Pitsillides A (2016) Mobile phone computing and the internet of things: a survey. IEEE Internet of Things J 3(6):885–898
Curry E, Guyon B, Sheridan C, Donnellan B (2012) Developing a sustainable IT capability: lessons from Intel’s journey. MIS Q Executive 11(2):61–74
Arshad R, Zahoor S, Shah MA, Wahid A, Yu H (2017) Green IoT: an investigation on energy saving practices for 2020 and beyond. IEEE Access 5:667–681
Mineraud J, Mazhelis O, Su X, Tarkoma S (2016) A gap analysis of internet-of-things platforms. Comput Commun 89:5–16
Wang HI (2014) Constructing the green campus within the internet of things architecture. Int J Distrib Sens Netw 10(3):1–8
Wang K, Wang Y, Sun Y, Guo S, Wu J (2016) Green industrial internet of things architecture: an energy-efficient perspective. IEEE Comm Mag 54(12):48–54
Moreno MV, Ãbeda B, Skarmeta AF, Zamora MA (2014) How can we tackle energy efficiency in IoT based smart buildings? Sensors 14(6):9582–9614
Palo HK, Mohanty MN, Chandra M (2018) Speech emotion recognition of different age groups using clustering analysis. Int J Inf Retrieval Res 8(1):69–85
Palo HK, Mohanty MN, Chandra M (2017) Emotion analysis from speech of different age groups. In: Proceedings of the second international conference on research in intelligent and computing in engineering, vol 10, pp 283–287
Keertikumar M, Shubham M, Banakar RM (2015) Evolution of IoT in smart vehicles: an overview. In: IEEE international conference on green computing and internet of things (ICGCIoT), pp 804–809
Md. AbdusSamad K, Jun I, Tomohisa H, Akira O, Kazuyuki A (2014) Smart driving of a vehicle using model predictive control for improving traffic flow. IEEE Trans Intell Transp Syst 15(2):1–11
Izquierdo MZ, Santa AJ, Gómez-Skarmeta AF (2010) An integral and networked home automation solution for indoor ambient intelligence. IEEE Pervasive Comput 9(4):66–77
Palo HK, Chandra M, Mohanty MN (2018) Recognition of human speech emotion using variants of mel-frequency cepstral coefficients. In: Advances in systems, control and automation, lecture notes in electrical engineering, vol 442. Springer Nature Singapore, pp 491–498
Palo HK, Kumar P, Mohanty MN (2017) Emotional speech recognition using optimized features. Int J Res Electron Comput Eng 5(4):4–9
Galinina O, Mikhaylov K, Andreev S, Turlikov A, Koucheryavy Y (2015) Smart home gateway system over Bluetooth low energy with wireless energy transfer capability. EURASIP J Wireless Comm Netw 1:1–18
Gou Q, Yan L, Liu Y, Li Y (2013) Construction and strategies in IoT security system. In: IEEE international conference on green computing and communications and IEEE internet of things and IEEE cyber, physical and social computing, pp 1129–1132
Shi W, Cao J, Zhang Q, Li Y, Xu L (2016) Edge computing: vision and challenges. IEEE Internet of Things J 3(5):637–646
Sun X, Ansari N (2016) EdgeIoT: mobile edge computing for the internet of things. IEEE Comm Mag 54(12):22–29
EPA Office Building Energy Use Profile (PDF). EPA. August 15, 2007. Archived from the original (PDF) on 6 Mar 2009, Retrieved 17 Mar 2008
Yi S, Hao Z, Qin Z, Li Q (2015) Fog computing: platform and applications. In: Proceedings of 3rd IEEE workshop hot topics web system and technology (HotWeb), Washington, DC, USA, pp 73–78
Atlam H, Walters R, Wills G (2018) Fog computing and the internet of things: a review. Big Data Cogn Comput 2(2):10
Al-Azez T, Lawey AQ, El-Gorashi TEH, Elmirghani JMH (2015) Virtualization framework for energy efficient IoT networks. In: Proceedings of IEEE 4th international conference on cloud network (CloudNet), pp 74–77
Colella R, Catarinucci L, Tarricone L (2016) Improved RFID tag characterization system: use case in the IoT arena. In: IEEE international conference on RFID technology and applications (RFID-TA), Foshan, pp 172–176
Peoples C, Parr G, McClean S, Scotney B, Morrow P (2013) Performance evaluation of green data center management supporting sustainable growth of the internet of things. Simul Model Pract Theory 34:221–242
Mirlacher T, Buchner R, Förster F, Weiss A, Tscheligi M (2009) Ambient rabbits likeability of embodied ambient displays. In: European conference on ambient intelligence. Springer, Berlin, pp 164–173
Mikusz M, Houben S, Davies N, Moessner K, Langheinrich M (2018) Raising awareness of IoT sensor deployments
Mohammadi M, Al-Fuqaha A, Sorour S, Guizani M (2018) Deep learning for IoT big data and streaming analytics: a survey. IEEE Commun Surv Tutorials 20(4):2923–2960
Venkataramani S, Roy K, Raghunathan A (2016) Efficient embedded learning for IoT devices. In: 21st Asia and South Pacific design automation conference (ASP-DAC). IEEE, pp 308–311
Ghimire S, Luis-Ferreira F, Nodehi T, Jardim-Goncalves R (2017) IoT based situational awareness framework for real-time project management. Int J Comput Integr Manuf 30(1):74–83
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Das, S.K., Palo, H.K. (2020). Internet of Things (IoT) Application in Green Computing: An Overview. In: Bhoi, A., Sherpa, K., Kalam, A., Chae, GS. (eds) Advances in Greener Energy Technologies. Green Energy and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-15-4246-6_4
Download citation
DOI: https://doi.org/10.1007/978-981-15-4246-6_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-4245-9
Online ISBN: 978-981-15-4246-6
eBook Packages: EnergyEnergy (R0)