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The Web of Things Ecosystem

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Abstract

The Internet of Things (IoT) ecosystem is gradually changing our activities and social interactions through the wide scale of applications it offers. However, these applications rely on the networking protocol stack where the application layer of the stack is implemented differently by different applications. As a result, a variety of data representation and diverse application layer protocols can be found in place adopted by a range of IoT-based services. This creates the issue of interoperability and scalability. Web of Things is a concept that interestingly applies the Web technologies to IoT-based applications. This chapter introduces the concept of the Web of Things, reviews its application potential, and discusses the details of forming such an ecosystem.

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References

  • AirVisual. Retrieved from https://www.prnewswire.com/news-releases/crowdsourced-air-quality-monitoring-network-revolutionizes-environmental-reporting-through-distributed-sensors-producing-the-worlds-largest-air-pollution-dataset-300443335.html

  • Alshamsi, A., Anwar, Y., Almulla, M., Aldohoori, M., Hamad, N., & Awad, M. (2017, November). Monitoring pollution: Applying IoT to create a smart environment. In 2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA) (pp. 1–4). IEEE.

    Google Scholar 

  • Ayaz, M., Ammad-Uddin, M., Sharif, Z., Mansour, A., & Aggoune, E. H. M. (2019). Internet-of-Things (IoT)-based smart agriculture: Toward making the fields talk. IEEE Access, 7, 129551–129583.

    Article  Google Scholar 

  • Barka, E., Mathew, S. S., & Atif, Y. (2015, May). Securing the web of things with role-based access control. In International Conference on Codes, Cryptology, and Information Security (pp. 14–26). Cham: Springer.

    Google Scholar 

  • Beza, E., Silva, J. V., Kooistra, L., & Reidsma, P. (2017). Review of yield gap explaining factors and opportunities for alternative data collection approaches. European Journal of Agronomy, 82, 206–222.

    Article  Google Scholar 

  • Catarinucci, L., De Donno, D., Mainetti, L., Palano, L., Patrono, L., Stefanizzi, M. L., & Tarricone, L. (2015). An IoT-aware architecture for smart healthcare systems. IEEE Internet of Things Journal, 2(6), 515–526.

    Article  Google Scholar 

  • Chowdhury, C., & Roy, S. (2017). Mobile crowd-sensing for smart cities. In Smart cities: Foundations, principles and applications (pp. 125–154). Wiley. ISBN: 978-1-119-22639-0.

    Google Scholar 

  • Crowdsourcing in Education. Retrieved from https://ideascalenation.medium.com/three-real-world-examples-of-crowdsourcing-in-education-ae470d3a8ef6

  • Crowdsourcing in Healthcare. Retrieved from https://medicalfuturist.com/crowdsourcing-in-digital-health/

  • Crowdsourcing in Industry. Retrieved from https://tweakyourbiz.com/marketing/9-great-examples-crowdsourcing-age-empowered-consumers

  • Dutta, J., Roy, S., & Chowdhury, C. (2019). Unified framework for IoT and smartphone based different smart city related applications. Microsystem Technologies, 25(1), 83–96.

    Article  Google Scholar 

  • Fernández-Caramés, T. M., & Fraga-Lamas, P. (2018). A review on human-centered IoT-connected smart labels for the industry 4.0. IEEE Access, 6, 25939–25957.

    Article  Google Scholar 

  • Google Wallet. (2013). Google Wallet 2013. Retrieved from http://www.google.com/wallet/

  • Govindraj, V., Sathiyanarayanan, M., & Abubakar, B. (2017, August). Customary homes to smart homes using Internet of Things (IoT) and mobile application. In 2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon) (pp. 1059–1063). IEEE.

    Google Scholar 

  • Grønli, T. M., Pourghomi, P., & Ghinea, G. (2015). Towards NFC payments using a lightweight architecture for the Web of Things. Computing, 97(10), 985–999.

    Article  MathSciNet  Google Scholar 

  • Guinard, D., & Trifa, V. (2009, April). Towards the web of things: Web mashups for embedded devices. In Workshop on Mashups, Enterprise Mashups and Lightweight Composition on the Web (MEM 2009), in proceedings of WWW (International World Wide Web Conferences), Madrid, Spain (Vol. 15, p. 8).

    Google Scholar 

  • Guinard, D., Trifa, V., & Wilde, E. (2010, November). A resource oriented architecture for the web of things. In 2010 Internet of Things (IOT) (pp. 1–8). IEEE.

    Google Scholar 

  • Guinard, D., Trifa, V., Mattern, F., & Wilde, E. (2011a). From the Internet of Things to the web of things: Resource-oriented architecture and best practices. In Architecting the Internet of Things (pp. 97–129). Berlin: Springer.

    Google Scholar 

  • Guinard, D., Ion, I., & Mayer, S. (2011b, December). In search of an internet of things service architecture: REST or WS-*? A developers’ perspective. In International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services (pp. 326–337). Berlin: Springer.

    Google Scholar 

  • Hoque, M. A., & Davidson, C. (2019). Design and implementation of an IoT-based smart home security system. International Journal of Networked and Distributed Computing, 7(2), 85–92.

    Article  Google Scholar 

  • Hoyos, J. R., Preuveneers, D., & García-Molina, J. J. (2017, June). Quality parameters as modeling language abstractions for context-aware applications: An AAL case study. In International and Interdisciplinary Conference on Modeling and Using Context (pp. 569–581). Cham: Springer.

    Google Scholar 

  • https://digital.hbs.edu/platform-rctom/submission/how-crowdsourcing-is-changing-the-waze-we-drive/

  • Huang, J., Duan, N., Ji, P., Ma, C., Ding, Y., Yu, Y., Zhou, Q., & Sun, W. (2018). A crowdsource-based sensing system for monitoring fine-grained air quality in urban environments. IEEE Internet of Things Journal, 6(2), 3240–3247.

    Article  Google Scholar 

  • Huang, D. Y., Apthorpe, N., Li, F., Acar, G., & Feamster, N. (2020). IoT inspector: Crowdsourcing labeled network traffic from smart home devices at scale. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4(2), 1–21.

    Article  Google Scholar 

  • Jain, S., Gupta, C., & Bhardwaj, A. (2016, December). Research directions under the parasol of ontology based semantic web structure. In International Conference on Soft Computing and Pattern Recognition (pp. 644–655). Cham: Springer.

    Google Scholar 

  • Javaid, S., Sufian, A., Pervaiz, S., & Tanveer, M. (2018, February). Smart traffic management system using Internet of Things. In 2018 20th International Conference on Advanced Communication Technology (ICACT) (pp. 393–398). IEEE.

    Google Scholar 

  • Joyent Inc. (2013). Node.js: Evented I/O for JavaScript. Retrieved from: http://nodejs.org/

  • Kincaid, J. (2010). Googles open spot makes parking a breeze, assuming everyone turns into a Good Samaritan. Retrieved from https://techcrunch.com/2010/07/09/google-Parking-Open-Spot/

  • Klinov, P., & Mouromtsev, D., (Eds.). (2015). Knowledge Engineering and Semantic Web: 6th International Conference, KESW 2015, Moscow, Russia, September 30-October 2, 2015, Proceedings (Vol. 518). Springer.

    Google Scholar 

  • Kodali, R. K., Rajanarayanan, S. C., & Boppana, L. (2020, January). IoT based smart wearable for air quality monitoring. In 2020 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1–5). IEEE.

    Google Scholar 

  • Leiba, B. (2012). Oauth web authorization protocol. IEEE Internet Computing, 16(1), 74–77.

    Article  Google Scholar 

  • Li, H., Pei, L., Liao, D., Zhang, M., Xu, D., & Wang, X. (2020). Achieving privacy protection for crowdsourcing application in edge-assistant vehicular networking. Telecommunication Systems: Modelling, Analysis, Design and Management, 1–14.

    Google Scholar 

  • Lookmuang, R., Nambut, K., & Usanavasin, S. (2018, May). Smart parking using IoT technology. In 2018 5th International Conference on Business and Industrial research (ICBIR) (pp. 1–6). IEEE.

    Google Scholar 

  • Mahalank, S. N., Malagund, K. B., & Banakar, R. M. (2016, March). Device to device interaction analysis in IoT based smart traffic management system: An experimental approach. In 2016 Symposium on Colossal Data Analysis and Networking (CDAN) (pp. 1–6). IEEE.

    Google Scholar 

  • Majeed, A., & Ali, M. (2018, January). How Internet-of-Things (IoT) making the university campuses smart? QA higher education (QAHE) perspective. In 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 646–648). IEEE.

    Google Scholar 

  • Manikandan, R., Patan, R., Gandomi, A. H., Sivanesan, P., & Kalyanaraman, H. (2020). Hash polynomial two factor decision tree using IoT for smart health care scheduling. Expert Systems with Applications, 141, 112924.

    Article  Google Scholar 

  • MasterCard PayPass. (2013). Just tap and go 2013. Retrieved from https://www.paypass.com/

  • MasterPass. (2013). Introducing MasterPass 2013. Retrieved from https://masterpass.com/

  • Mavakala, B., Mulaji, C., Mpiana, P., Elongo, V., Otamonga, J. P., Biey, E., Wildi, W., Pote-Wembonyama, J., & Giuliani, G. (2017). Citizen sensing of solid waste disposals: Crowdsourcing as tool supporting waste management in a developing country. In Proceedings Sardinia 2017/Sixteenth International Waste Management and Landfill Symposium.

    Google Scholar 

  • Minet, J., Curnel, Y., Gobin, A., Goffart, J. P., Melard, F., Tychon, B., Wellens, J., & Defourny, P. (2017). Crowdsourcing for agricultural applications: A review of uses and opportunities for a farmsourcing approach. Computers and Electronics in Agriculture, 142, 126–138.

    Article  Google Scholar 

  • Mishra, S., & Jain, S. (2020). Ontologies as a semantic model in IoT. International Journal of Computers and Applications, 42(3), 233–243.

    Article  Google Scholar 

  • Mishra, S., Jain, S., Rai, C., & Gandhi, N. (2018, December). Security challenges in semantic Web of Things. In International Conference on Innovations in Bio-Inspired Computing and Applications (pp. 162–169). Cham: Springer.

    Google Scholar 

  • Misra, D., Das, G., Chakrabortty, T., & Das, D. (2018). An IoT-based waste management system monitored by cloud. Journal of Material Cycles and Waste Management, 20(3), 1574–1582.

    Article  Google Scholar 

  • Mitra, N., & Lafon, Y. (2003). Soap version 1.2 part 0: Primer. W3C Recommendation, 24, 12.

    Google Scholar 

  • Mumbaikar, S., & Padiya, P. (2013). Web services based on soap and rest principles. International Journal of Scientific and Research Publications, 3(5), 1–4.

    Google Scholar 

  • Munasinghe, M. I. N. P., Perera, G. I. U. S., Karunathilaka, J. K. W. D. B., Cooray, B. C. S., & Manupriyal, K. G. D. (2017). Air pollution monitoring through crowdsourcing. In 111th annual sessions of the IESL, Colombo.

    Google Scholar 

  • Mutembesa, D., Omongo, C., & Mwebaze, E. (2018, June). Crowdsourcing real-time viral disease and pest information: A case of nation-wide cassava disease surveillance in a developing country. In Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (Vol. 6, no. 1).

    Google Scholar 

  • Nie, Y., Xu, K., Chen, H., & Peng, L. (2019, October). Crowd-parking: A new idea of parking guidance based on crowdsourcing of parking location information from automobiles. In IECON 2019-45th Annual Conference of the IEEE Industrial Electronics Society (Vol. 1, pp. 2779–2784). IEEE.

    Google Scholar 

  • Oh, S. W., & Kim, H. S. (2014, February). Decentralized access permission control using resource-oriented architecture for the Web of Things. In 16th International Conference on Advanced Communication Technology (pp. 749–753). IEEE.

    Google Scholar 

  • Patel, A., & Jain, S. (2019). Present and future of semantic web technologies: A research statement. International Journal of Computers and Applications, 1–10.

    Google Scholar 

  • Pilloni, V. (2018). How data will transform industrial processes: Crowdsensing, crowdsourcing and big data as pillars of industry 4.0. Future Internet, 10(3), 24.

    Google Scholar 

  • Rahman, M., Blackwell, B., Banerjee, N., & Saraswat, D. (2015). Smartphone-based hierarchical crowdsourcing for weed identification. Computers and Electronics in Agriculture, 113, 14–23.

    Article  Google Scholar 

  • Saha, A., Chowdhury, C., Jana, M., & Biswas, S. (2020). IoT sensor data analysis and fusion applying machine learning and meta-heuristic approaches. In Enabling AI applications in data science (pp. 441–469).

    Google Scholar 

  • Saif, S., Datta, D., Saha, A., Biswas, S., & Chowdhury, C. (2020). Data science and AI in IoT based smart healthcare: Issues, challenges and case study. In Enabling AI Applications in Data Science (pp. 415–439). Cham: Springer.

    Google Scholar 

  • Saraf, S. B., & Gawali, D. H. (2017, May). IoT based smart irrigation monitoring and controlling system. In 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) (pp. 815–819). IEEE.

    Google Scholar 

  • Serena, F., Poveda-Villalón, M., & García-Castro, R. (2017, June). Semantic discovery in the web of things. In International Conference on Web Engineering (pp. 19–31). Cham: Springer.

    Google Scholar 

  • SFMTA. SFPark-About the Project. Retrieved from https://www.sfmta.com/demand-responsive-parking-pricing

  • Shu, L., Chen, Y., Huo, Z., Bergmann, N., & Wang, L. (2017). When mobile crowd sensing meets traditional industry. IEEE Access, 5, 15300–15307.

    Article  Google Scholar 

  • Simic, K., Despotovic-Zrakic, M., Ðuric, I., Milic, A., & Bogdanovic, N. (2015). A model of smart environment for e-learning based on crowdsourcing. RUO. Revija za Univerzalno Odlicnost, 4(1), A1.

    Google Scholar 

  • Singh, S., Mehta, K. S., Bhattacharya, N., Prasad, J., Lakshmi, S. K., Subramaniam, K. V., & Sitaram, D. (2017, July). Identifying uncollected garbage in urban areas using crowdsourcing and machine learning. In 2017 IEEE Region 10 Symposium (TENSYMP) (pp. 1–5). IEEE.

    Google Scholar 

  • Suresh, S., Sharma, T., & Sitaram, D. (2016, December). Towards quantifying the amount of uncollected garbage through image analysis. In Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing (pp. 1–8).

    Google Scholar 

  • Wazny, K. (2018). Applications of crowdsourcing in health: An overview. Journal of Global Health, 8(1).

    Google Scholar 

  • WOT GROUP. Retrieved from https://www.w3.org/WoT/wg/

  • Wu, Z., Xu, Y., Zhang, C., Yang, Y., & Ji, Y. (2016, July). Towards semantic web of things: From manual to semi-automatic semantic annotation on web of things. In International Conference on Big Data Computing and Communications (pp. 295–308). Cham: Springer.

    Google Scholar 

  • Xie, W., Tang, Y., Chen, S., Zhang, Y., & Gao, Y. (2016, September). Security of web of things: A survey (short paper). In International Workshop on Security (pp. 61–70). Cham: Springer.

    Google Scholar 

  • Yu, J., Bang, H. C., Lee, H., & Lee, Y. S. (2016). Adaptive Internet of Things and Web of Things convergence platform for Internet of reality services. The Journal of Supercomputing, 72(1), 84–102.

    Article  Google Scholar 

  • Zeng, D., Guo, S., & Cheng, Z. (2011). The web of things: A survey. JCM, 6(6), 424–438.

    Article  Google Scholar 

  • Zhu, C., Mehrabi, A., Xiao, Y., & Wen, Y. (2019, September). CrowdParking: Crowdsourcing based parking navigation in autonomous driving era. In 2019 International Conference on Electromagnetics in Advanced Applications (ICEAA) (pp. 1401–1405). IEEE.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Information Technology, Techno Main Salt Lake, Kolkata, West Bengal, India

    Anindita Saha

  2. Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, Kolkata, India

    Mayurakshi Jana & Suparna Biswas

  3. Computer Science and Engineering, Jadavpur University, Kolkata, India

    Chandreyee Chowdhury

  4. Teesside University, Middlesbrough, UK

    Diptangshu Pandit

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  1. Anindita Saha
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  2. Mayurakshi Jana
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  3. Chandreyee Chowdhury
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  4. Suparna Biswas
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  5. Diptangshu Pandit
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Editors and Affiliations

  1. National Institute of Technology, Kurukshetra, India

    Sarika Jain

  2. BRITE Professional Services, Sydney, Australia

    San Murugesan

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Saha, A., Jana, M., Chowdhury, C., Biswas, S., Pandit, D. (2021). The Web of Things Ecosystem. In: Jain, S., Murugesan, S. (eds) Smart Connected World. Springer, Cham. https://doi.org/10.1007/978-3-030-76387-9_3

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