phd thesis on iot pdf

February 5th, 2020

DSpace JSPUI

Dspace preserves and enables easy and open access to all types of digital content including text, images, moving images, mpegs and data sets.

• Newcastle University eTheses
• Newcastle University
• Faculty of Science, Agriculture and Engineering
• School of Computing Science

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

The Role of the Internet of Things (IoT) in Transforming the Business Model of Small and Medium Enterprises (SMEs)

Sample Thesis Introduction

Chapter 1: Introduction

1.1. existing research gaps.

With the world becoming more interconnected and the increasing disruptiveness of information technology, the concept of the internet of things (IoT) has become an important research topic (Ehret & Wirtz, 2017, 1). Given the growing acceptability of IoT, organisations are now prompted to adopt IoT solutions to improve and enhance the experience of their customers and clients (Metallo, Agrifoglio, Schiavone & Mueller, 2018, 298). In accordance with Kiel, Arnold & Voigt (2017, 4), IoT crates a network of interconnected physical devices, which exchange data with each other through the internet, allowing enterprises to obtain and use strategic information (Gierej, 2017, 206). The existing marketing literature has shed some light on the effects of IoT on consumer behaviour and its contribution to the creation of new business opportunities (Boyes, Hallaq, Cunningham & Watson, 2018, 1). In contrast, there is no much empirical evidence on how IoT helps companies deal with external and internal challenges by altering their business models (Lu, Papagiannidis & Alamanos, 2018, 285). Considering the uncertainties of IoT as well as the relative novelty of this concept, the significance and importance of business models that allow organisations to shield their customers and clients against external fluctuations and changes should be further investigated. This project contributes to bridging this gap in the literature by providing the reader with a deeper understanding of the opportunities and threats offered by IoT and its role in business model change in the context of small and medium enterprises (SMEs).

1.2. Rationale

The topic of IoT is of particular interest to the researcher due to a range of reasons. One of these causes is that the significance of relationship marketing has dramatically increased with the emergence of IoT (Glova, Sabol & Vajda, 2014, 1122). Today, marketers are striving towards the establishment of long-term relationships with consumers, instead of simply stimulating their intention to buy (Krotov, 2017, 831). The role of IoT in this process is considerable as the internet and mobile devices have being increasingly used for communication purposes by both consumers and businesses (Ehret & Wirtz, 2017, 1). The growing presence of IoT translates into more sophisticated and effective marketing strategies, which tend to use such instruments as neural networks and artificial intelligence (AI) (Kiel et al., 2017, 4). Nonetheless, the literature that examines how companies make use of the technological potential of IoT for organisational design is still fragmented and insufficient (Alexopoulos, Koukas, Boli & Mourtzis, 2018, 880). Another reason for choosing this particular topic is that the pace at which IoT develops makes the majority of standard business models adopted by SMEs unsatisfactory (Metallo et al., 2018, 298). Hence, there is a strong urge to understand how the potential business opportunities and threats created by IoT can lead to reorganisation activities aimed at the SMEs’ business models.

1.3. Thesis Background

IoT research has been predominantly stimulated by the need for convergence in a range of interdisciplinary technologies (Wang & Hsieh, 2018, 28). To get a better understanding of the relationship between IoT and the business model, it is relevant to have a closer look at what constitutes the internet of things. The IoT landscape comprises three major dimensions or environments, namely technological environment, physical environment, and socio-economic environment (Gierej, 2017, 206). The technological environment consists of such elements as hardware, software, data, networking technologies, and integrated platforms, which enable communication and interactions of the objects in the physical environment (Babiceanu & Seker, 2019, 47). In turn, the physical environment is comprised of human and non-human objects that are linked together by means of the previously mentioned elements of the technological environment (Lu et al., 2018, 285). Finally, the socio-economic environment consists of various stakeholders (e.g. consumers, entrepreneurs, legislative bodies, and industry associations) that set requirements, address technical and legal issues, and determine the success or failure of a business entity (Krotov, 2017, 831). By using these dimensions and their elements in combination, SMEs can create new value propositions or business models with the help of IoT. However, the success and effectiveness of these enhanced business models depends on how well organisations address IoT-driven threats that exist in the external environment (Boyes et al., 2018, 1). These threats can include challenges of information and data reliability, potential market disruption by new competition, intellectual property risks, and safety and security issues (Ehret & Wirtz, 2017, 1).

1.4. Aim and Objectives

Based on the identified research and literature gaps, the main purpose of this doctorate project is to explore the role of IoT in transforming the business model in the context of SMEs. The research objectives are:

• To examine the key elements of the IoT landscape and connections between them.
• To identify the role of IoT in the value creation process in the context of SMEs.
• To explore the impact of IoT on SMEs’ business models.
• To investigate SMEs’ response to business opportunities and threats generated by IoT.
• To provide SMEs’ management with recommendations on what particular improvements could be introduced to their business model to make it more responsive to the recent IoT trends.

1.5. Suggested Methods

This doctorate project employs a mixed method approach, which is justified by the fact that no sufficient research on the relationship between IoT and business models in the contexts of SMEs exists (Kiel et al., 2017, 4). The sample was drawn from 250 managers and owners of UK-based SMEs. Semi-structured interviews with these individuals formed the principal source of empirical data (Merriam, 2015, 134). While collecting data occurs in a structured manner, this technique still allows for following the principle of openness (Howell, 2012, 93). In turn, the researcher employed self-administered questionnaires to explore what elements of the IoT landscape the sampled SMEs use the most. In addition, this technique helped the researcher investigate the respondents’ perceptions of the key opportunities and threats created by IoT (Lo & Campos, 2018, 10). The researcher performed sampling by using the non-probability convenience sampling technique, thereby allowing for collecting data in a fast and efficient manner (Pruzan, 2016, 79). By contrast, the use of this technique could negatively influence the generalisability of the obtained empirical findings (Bryman & Bell, 2010, 142).

Alexopoulos, K., Koukas, S., Boli, N. & Mourtzis, D. (2018). “Architecture and development of an Industrial Internet of Things framework for realizing services in Industrial Product Service Systems”. Procedia CIRP , 72(1), 880-885.

Babiceanu, R. & Seker, R. (2019). “Cyber resilience protection for industrial internet of things: A software-defined networking approach”. Computers in Industry , 104(1), 47-58.

Boyes, H., Hallaq, B., Cunningham, J. & Watson, T. (2018). “The industrial internet of things (IIoT): An analysis framework”. Computers in Industry , 101(1), 1-12.

Bryman, A. & Bell, E. (2010). Business research methods . 3 rd ed., Oxford: Oxford University Press.

Ehret, M. & Wirtz, J. (2017). “Unlocking value from machines: Business models and the industrial internet of things”. Journal of Marketing Management , 33(1-2), 1-20.

Gierej, S. (2017). “The framework of business model in the context of Industrial Internet of Things”. Procedia Engineering , 182(1), 206-212.

Glova, J., Sabol, T. & Vajda, V. (2014). “Business models for the internet of things environment”. Procedia Economics and Finance , 15(1), 1122-1129.

Howell, K. (2012). An introduction to the philosophy of methodology . London: SAGE.

Kiel, D., Arnold, C. & Voigt, K. (2017). “The influence of the Industrial Internet of Things on business models of established manufacturing companies–A business level perspective”. Technovation , 68(1), 4-19.

Krotov, V. (2017). “The Internet of Things and new business opportunities”. Business Horizons , 60(6), 831-841.

Lo, F. & Campos, N. (2018). “Blending Internet-of-Things (IoT) solutions into relationship marketing strategies”. Technological Forecasting and Social Change , 137(1), 10-18.

Lu, Y., Papagiannidis, S. & Alamanos, E. (2018). “Internet of Things: A systematic review of the business literature from the user and organisational perspectives”. Technological Forecasting and Social Change , 136(1), 285-297.

Merriam, S. (2015). Qualitative research: A guide to design and implementation . Chichester: John Wiley & Sons.

Metallo, C., Agrifoglio, R., Schiavone, F. & Mueller, J. (2018). “Understanding business model in the Internet of Things industry”. Technological Forecasting and Social Change , 16(1), 298-306.

Pruzan, P. (2016). Research Methodology: The Aims, Practices and Ethics of Science . New York: Springer.

Wang, Y. & Hsieh, C. (2018). “Explore technology innovation and intelligence for IoT (Internet of Things) based eyewear technology”. Technological Forecasting and Social Change , 127(1), 281-290.

• Email Alert

论文  全文  图  表  新闻 

• Abstracting/Indexing
• Journal Metrics
• Current Editorial Board
• Early Career Advisory Board
• Previous Editor-in-Chief
• Past Issues
• Current Issue
• Special Issues
• Early Access
• Online Submission
• Information for Authors
• Share facebook twitter google linkedin

IEEE/CAA Journal of Automatica Sinica

• JCR Impact Factor: 11.8 , Top 4% (SCI Q1) CiteScore: 17.6 , Top 3% (Q1) Google Scholar h5-index: 77， TOP 5

Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

Doi:  10.1109/jas.2021.1003925.

• Othmane Friha 1 ,  , 
• Mohamed Amine Ferrag 2 ,  , 
• Lei Shu 3, 4 ,  ,  , 
• Leandros Maglaras 5 ,  , 
• Xiaochan Wang 6 , 

Networks and Systems Laboratory, University of Badji Mokhtar-Annaba, Annaba 23000, Algeria

Department of Computer Science, Guelma University, Gulema 24000, Algeria

College of Engineering, Nanjing Agricultural University, Nanjing 210095, China

School of Engineering, University of Lincoln, Lincoln LN67TS, UK

School of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, UK

Department of Electrical Engineering, Nanjing Agricultural University, Nanjing 210095, China

Othmane Friha received the master degree in computer science from Badji Mokhtar-Annaba University, Algeria, in 2018. He is currently working toward the Ph.D. degree in the University of Badji Mokhtar-Annaba, Algeria. His current research interests include network and computer security, internet of things (IoT), and applied cryptography

Mohamed Amine Ferrag received the bachelor degree (June, 2008), master degree (June, 2010), Ph.D. degree (June, 2014), HDR degree (April, 2019) from Badji Mokhtar-Annaba University, Algeria, all in computer science. Since October 2014, he is a Senior Lecturer at the Department of Computer Science, Guelma University, Algeria. Since July 2019, he is a Visiting Senior Researcher, NAULincoln Joint Research Center of Intelligent Engineering, Nanjing Agricultural University. His research interests include wireless network security, network coding security, and applied cryptography. He is featured in Stanford University’s list of the world’s Top 2% Scientists for the year 2019. He has been conducting several research projects with international collaborations on these topics. He has published more than 60 papers in international journals and conferences in the above areas. Some of his research findings are published in top-cited journals, such as the IEEE Communications Surveys and Tutorials , IEEE Internet of Things Journal , IEEE Transactions on Engineering Management , IEEE Access , Journal of Information Security and Applications (Elsevier), Transactions on Emerging Telecommunications Technologies (Wiley), Telecommunication Systems (Springer), International Journal of Communication Systems (Wiley), Sustainable Cities and Society (Elsevier), Security and Communication Networks (Wiley), and Journal of Network and Computer Applications (Elsevier). He has participated in many international conferences worldwide, and has been granted short-term research visitor internships to many renowned universities including, De Montfort University, UK, and Istanbul Technical University, Turkey. He is currently serving on various editorial positions such as Editorial Board Member in Journals (Indexed SCI and Scopus) such as, IET Networks and International Journal of Internet Technology and Secured Transactions (Inderscience Publishers)

Lei Shu (M’07–SM’15) received the B.S. degree in computer science from South Central University for Nationalities in 2002, and the M.S. degree in computer engineering from Kyung Hee University, South Korea, in 2005, and the Ph.D. degree from the Digital Enterprise Research Institute, National University of Ireland, Ireland, in 2010. Until 2012, he was a Specially Assigned Researcher with the Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University, Japan. He is currently a Distinguished Professor with Nanjing Agricultural University and a Lincoln Professor with the University of Lincoln, U.K. He is also the Director of the NAU-Lincoln Joint Research Center of Intelligent Engineering. He has published over 400 papers in related conferences, journals, and books in the areas of sensor networks and internet of things (IoT). His current H-index is 54 and i10-index is 197 in Google Scholar Citation. His current research interests include wireless sensor networks and IoT. He has also served as a TPC Member for more than 150 conferences, such as ICDCS, DCOSS, MASS, ICC, GLOBECOM, ICCCN, WCNC, and ISCC. He was a Recipient of the 2014 Top Level Talents in Sailing Plan of Guangdong Province, China, the 2015 Outstanding Young Professor of Guangdong Province, and the GLOBECOM 2010, ICC 2013, ComManTel 2014, WICON 2016, SigTelCom 2017 Best Paper Awards, the 2017 and 2018 IEEE Systems Journal Best Paper Awards, the 2017 Journal of Network and Computer Applications Best Research Paper Award, and the Outstanding Associate Editor Award of 2017, and the 2018 IEEE ACCESS. He has also served over 50 various Co-Chair for international conferences/workshops, such as IWCMC, ICC, ISCC, ICNC, Chinacom, especially the Symposium Co-Chair for IWCMC 2012, ICC 2012, the General Co-Chair for Chinacom 2014, Qshine 2015, Collaboratecom 2017, DependSys 2018, and SCI 2019, the TPC Chair for InisCom 2015, NCCA 2015, WICON 2016, NCCA 2016, Chinacom 2017, InisCom 2017, WMNC 2017, and NCCA 2018

Leandros Maglaras (SM’15) received the B.Sc. degree from Aristotle University of Thessaloniki, Greece, in 1998, M.Sc. in industrial production and management from University of Thessaly in 2004, and M.Sc. and Ph.D. degrees in electrical & computer engineering from University of Volos in 2008 and 2014, respectively. He is the Head of the National Cyber Security Authority of Greece and a Visiting Lecturer in the School of Computer Science and Informatics at the De Montfort University, U.K. He serves on the Editorial Board of several International peer-reviewed journals such as IEEE Access , Wiley Journal on Security & Communication Networks , EAI Transactions on e-Learning and EAI Transactions on Industrial Networks and Intelligent Systems . He is an author of more than 80 papers in scientific magazines and conferences and is a Senior Member of IEEE. His research interests include wireless sensor networks and vehicular ad hoc networks

Xiaochan Wang is currently a Professor in the Department of Electrical Engineering at Nanjing Agricultural University. His main research fields include intelligent equipment for horticulture and intelligent measurement and control. He is an ASABE Member, and the Vice Director of CSAM (Chinese Society for Agricultural Machinery), and also the Senior Member of Chinese Society of Agricultural Engineering. He was awarded the Second Prize of Science and Technology Invention by the Ministry of Education (2016) and the Advanced Worker for Chinese Society of Agricultural Engineering (2012), and he also gotten the “Blue Project” in Jiangsu province young and middle-aged academic leaders (2010)

• Corresponding author: Lei Shu, e-mail: [email protected]
• Revised Date: 2020-11-25
• Accepted Date: 2020-12-30
• Agricultural internet of things (IoT) , 
• internet of things (IoT) , 
• smart agriculture , 
• smart farming , 
• sustainable agriculture

Proportional views

通讯作者: 陈斌, [email protected].

沈阳化工大学材料科学与工程学院 沈阳 110142

Figures( 12 )  /  Tables( 9 )

Article Metrics

• PDF Downloads( 2057 )
• Abstract views( 10801 )
• HTML views( 1388 )
• We review the emerging technologies used by the Internet of Things for the future of smart agriculture.
• We provide a classification of IoT applications for smart agriculture into seven categories, including, smart monitoring, smart water management, agrochemicals applications, disease management, smart harvesting, supply chain management, and smart agricultural practices.
• We provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward supply chain management based on the blockchain technology for agricultural IoTs.
• We highlight open research challenges and discuss possible future research directions for agricultural IoTs.
• Copyright © 2022 IEEE/CAA Journal of Automatica Sinica
• 京ICP备14019135号-24
• E-mail: [email protected]  Tel: +86-10-82544459, 10-82544746
• Address: 95 Zhongguancun East Road, Handian District, Beijing 100190, China

Export File

• Figure 1. The four agricultural revolutions
• Figure 2. Survey structure
• Figure 3. IoT-connected smart agriculture sensors enable the IoT
• Figure 4. The architecture of a typical IoT sensor node
• Figure 5. Fog computing-based agricultural IoT
• Figure 6. SDN/NFV architecture for smart agriculture
• Figure 7. Classification of IoT applications for smart agriculture
• Figure 8. Greenhouse system [ 101 ]
• Figure 9. Aerial-ground robotics system [ 67 ]
• Figure 10. Photovoltaic agri-IoT schematic diagram [ 251 ]
• Figure 11. Smart dairy farming system [ 254 ]
• Figure 12. IoT-based solar insecticidal lamp [ 256 ], [ 257 ]