RAINBOW Platform Stakeholder Analysis: Applications and markets that may benefit from RAINBOW outcomes

Below you can read a blog post authored by K3Y and originally published at the RAINBOW website.

Interests and relations, regarding the three categories of stakeholders which analysed in the Blog Post entitled RAINBOW Platform Stakeholder Analysis: The 3 Categories of Stakeholders”, were investigated further, in order to identify RAINBOW’s key stakeholders, in the Blog Post “RAINBOW Platform Stakeholder Analysis: RAINBOW’s key stakeholders“.

This analysis presents applications and markets that may benefit from RAINBOW outcomes:

Mobile Devices Applications and Gaming

The applications which fall into this category are specifically targeted at consumer’s mobile devices, such as smartphones, tablets or head-mounted devices. Mobile applications and gaming development are rapidly expanding and they are in a stage when they seek to provide an experience more immersive than ever before, by utilizing new devices such as headsets, smart glasses etc. and state of the art technologies such as Augmented Reality (AR) and Virtual Reality (VR)  [1]. Although some of the aforementioned concepts are already in the market, their exploitation and the market acceptance are under consideration since there are not many devices which can support them, because they are really demanding in terms of processing and storage resources. These requirements have led to the emergence of new business and deployment models such as Gaming as a Service (GaaS) [2]. GaaS is a concept that overcomes hardware
limitations through application modularization where a demanding functionality is migrated from the mobile device to a server, a concept that resembles the concept of Edge/fog technology. Edge/fog computing can take up the aforementioned challenges and thus it is expected to give a significant push to mobile applications and gaming industry.

Infrastructure Applications

The notion of infrastructure refers to infrastructure as basic services and facilities which the well-being of society depends on. Smart Grids [3], environmental monitoring [4], waste management [5], public safety and emergency response [6], smart transportation [7] and connected cars [8] are huge concepts that involve plenty of requirements such as real time processing, guaranteed QoS etc. Edge/fog seems an option which can take up the aforementioned challenges. As a result, it can be considered as a key technology in the deployment of concepts around smart cities [9] by facilitating information technology to augment critical infrastructures.

IoT Device Applications

Internet of Things (IoT) refers to objects that are connected and able to interact with each other and extend the Internet to the physical world [10]. IoT is a tremendous concept which can potentially cover every aspect of the human’s daily activity. Out of all IoT applications, smart agriculture, smart building [11] plus livestock [12] and industrial IoT [13] are three applications that are already utilized for enhancing efficiency, productivity, and resource saving. The data volume produced by these applications and the latency requirements they may subtend in some cases, will be likely to be critical in terms of transfer and processing at central clouds [14] [15]. Edge/fog computing can handle the delay sensitive tasks and some of the data volume in order to support such kind of applications.

Human Applications

They can be used to improve the wellbeing and capabilities of humans. Real time monitoring of human’s vital parameters [16] and precision medicine [17] are two types of the human-centric application that are already in the market and fall into the category of the connected health concept. Connected health is a sociotechnical model for healthcare management and delivery by using technology to provide healthcare services remotely which aims to maximize healthcare resources and provide increased, flexible opportunities for individuals to engage with clinicians and better self-manage their care [18]. Moreover, it brings together multidisciplinary technologies to provide preventive or remote treatments by utilizing digital heath information structure while at the same time connecting patients and caregivers seamlessly in the loop of the healthcare ecosystem. Privacy and data security are critical concerns in such kind of applications due to the intimate nature of the data. Today’s cloud-based services fail to take up these requirements [19] which implies the need for new technologies such as edge/fog which can deal with issues such as data integrity, authenticity, and confidentiality.

References

[1] J. Steuer, “Defining virtual reality: Dimensions determining telepresence,” J. Commun., vol. 42, no. 4, p. pp. 73–93, Dec. 2010.

 

[2] W. Cai, M. Chen and a. V. C. M. Leung, “Toward gaming as a service,” IEEE Internet Comput., vol. 18, no. 3, p. pp. 12–18, May/Jun. 2014

 

[3] S. Howell, Y. Rezgui, J. Hippolyte, B. Jayan and a. H. Li, “Towards the next generation of smart grids: Semantic and holonic multi-agent management of distributed energy resources,” Renew. Sustain. Energy Rev., vol. 77, p. pp. 193–214, Sep 2017.

 

[4] Y. Zheng, F. Liu and a. H. Hsieh, “U-Air: When urban air quality inference meets big data,,” in in Proc. 19th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining (KDD), 2013.

 

[5] T. Nuortio, J. Kytöjoki, H. Niska and a. O. Bräysy, “Improved route planning and scheduling of waste collection and transport,” Expert Syst. Appl.,vol. 30, no. 2, pp. pp. 223–232, 2006.

 

[6] C. Chung, D. Egan, A. Jain, N. Caruso, C. Misner and a. R. Wallace, “A cloud-based mobile computing applications platform for first responders,” in in Proc. 7th IEEE Int. Symp. Service-Oriented Syst. (SOSE), 2013.

 

[7] B. Ghazal, K. ElKhatib, K. Chahine and a. M. Kherfanin, “Smart traffic light control system,” in Proc. 3rd Int. Conf. Elect., Electron., Comput. Eng. Appl. (EECEA), Apr. 2016.

 

[8] Laberteaux and H. Hartenstein, “A tutorial survey on vehicular ad hoc networks,” IEEE Commun. Mag., vol. 46, no. 6, p. pp. 164–171, Jun. 2008.

 

[9] H. Schaffers, N. Komninos, M. Pallot, B. Trousse, M. Nilsson and a. A. Oliveira, “Smart cities and the future Internet: Towards cooperation frameworks for open innovation,” in Future Internet Future Internet Assembly 2011: Achievements and Technological Promises. Berlin, Germany: Springer, p. pp. 431–446., 2011.

 

[10] L. Atzori, A. Iera and a. G. Morabito, “The Internet of Things: A survey,” Comput. Netw., vol. 54, no. 15, p. pp. 2787–2805, Oct. 2010.

 

[11] M. Casini, “Internet of Things for energy efficiency of buildings,” Int.Sci. J. Archit. Eng., vol. 2, no. 1, pp. pp. 24–28, 2014.

 

[12] G. Kakamoukas, P. Sarigiannidis, G. Livanos, M. Zervakis, D. Ramnalis and V. Polychronos, “A Multi-collective, IoT-enabled, Adaptive Smart Farming Architecture.,” in 2019 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2019.

 

[13] J. Wan, B. Chen, S. Wang, M. Xia, D. Li and a. C. Liu, “Fog computing for energyaware load balancing and scheduling in smart factory,” IEEE Trans. Ind. Informat., vol. 14, no. 10, p. pp. 4548–4556.

 

[14] McElhannon and J. Pan, “Future edge cloud and edge computing for Internet of Things applications,” IEEE Internet Things J., vol. 5, no. 1, p. pp. 439–449, Feb. 2018.

 

[15] N. M. Sandar, S. Chaisiri, S. Yongchareon and a. V. Liesaputra, “Cloud-based video monitoring framework: An approach based on software-defined networking for addressing scalability problems,” in in Proc. Web Inf. Syst. Eng. (WISE) Workshops, 2014.

 

[16] J. Sherman and D. Nafus, “Big data, big questions| this one does not go up to 11: The quantified self movement as an alternative big data practice,” Int. J. Commun., vol. 8, no. 11, p. pp. 1784–1794, 2014.

 

[17] M. Zorzi and B. N., “Health care applications: A solution based on the Internet of Things,” in in Proc. 4th Int. Symp. Appl. Sci. Biomed. Commun. Technol. (ISABEL), 2011.

 

[18] Z. Gang and W. Honggang, “Connected Health,” IEEE Internet Computing, vol. 24, no. 2, pp. 5 – 7, 2020.

 

[19] H. Fereidooni, T. Frassetto, M. Miettinen, A. Sadeghi and M. Conti, “Fitness trackers: Fit for health but unfit for security and privacy,” in in Proc. IEEE/ACM Int. Conf. Connected Health, Appl., Syst. Eng. Technol. (CHASE), Jul. 2017

 

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