566 548
Full Length Article
Fusion: Practice and Applications
Volume 11 , Issue 2, PP: 08-20 , 2023 | Cite this article as | XML | Html |PDF

Title

Intelligent Decision Making in IoT-Based Enterprise Management through Fusion Optimization with Deep Learning Models

  Saif Saad Ahmed 1 * ,   Anwar Ja’afar M. Jawad 2 ,   Shorook K. Abd 3 ,   Aymen Mohammed 4 ,   Amjed Hameed Majeed 5

1  Al-Turath University College, Baghdad, 10021, Iraq
    (saif.saad@turath.edu.iq)

2  Department of Computer Techniques Engineering, Al-Rafidain University College, Baghdad 10064, Iraq
    (anwar.jawad@ruc.edu.iq)

3  Department of Computer Techniques Engineering, Mazaya University College, Thi Qar, Iraq
    (shurooqkamel7@gmail.com)

4  Department of Medical instruments engineering techniques, Alfarahidi University, Baghdad, Iraq
    (ayman.mohammed@alfarahidiun.edu.iq)

5  Business Administration Department, Al- Mustaqbal University College51001 Hillah, Babylon, Iraq
    (amjed_hameed@uomus.edu.iq)

Full Text Download


Doi   :   https://doi.org/10.54216/FPA.110201

Received: December 03, 2022 Accepted: April 01, 2023

Abstract :

Because of the proliferation of digital technologies, organizations now have access to previously unimaginable troves of data. In order to make educated choices and generate beneficial results, accurate data analysis and interpretation are essential. The use of data visualization in this context has proven its value. Recent studies found that data visualization increased business owners' drive to make a profit. To aid business owners in evaluating issues related to self-service data resources, a dynamic IoT-based enterprise management framework (IEMF-IDM) was presented. The suggested system uses fusion optimization techniques to maximize the fusion score and enhance decision-making through the use of various models and methods, such as machine learning and fuzzy approaches. Simulation studies in a number of domains, including robots, cloud settings, and multimedia data fusion, attest to the system's efficacy.

Keywords :

Internet of Things; Business Intelligence; Enterprise Management; Data Visualization; Fusion Optimization.

References :

[1]  Özemre, M., & Kabadurmus, O. (2020). A big data analytics based methodology for strategic decision making. Journal of Enterprise Information Management.

[2]  Nguyen, T. N., Liu, B. H., Nguyen, N. P., & Chou, J. T. (2020, June). Cyber security of smart grid: attacks and defenses. In ICC 2020-2020 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.

[3]  Fattahi, R., Tavakkoli-Moghaddam, R., Khalilzadeh, M., Shahsavari-Pour, N., & Soltani, R. (2020). A novel  FMEA  model  based  on  fuzzy  multiple-criteria  decision-making  methods  for  risk assessment. Journal of Enterprise Information Management.

[4]  Liu, B. H., Pham, V. T., Nguyen, T. N., & Luo, Y. S. (2019). A heuristic for maximizing the lifetime of data aggregation in wireless sensor networks. arXiv preprint arXiv:1910.05310.

[5]  Abd  Al-Aziz  Hosni  El-Bagoury  ,  Sundus  Naji  AL-Aziz  ,  S.S.ASKAR,  Social  Spider  Optimization Algorithm  with  Gradient  Boosting  Tree  Model  for  Decision  Making  in  Telemarketing  Sector, American  Journal  of  Business  and  Operations  Research,  Vol.  7  ,  No.  1  ,  (2022)  :  09-18  (Doi    : https://doi.org/10.54216/AJBOR.070101)

[6]  Kranthi Kumar Singamaneni , S V Bharath Kumar Reddy , U Sreenivasulu, A Novel Framework to Enterprise Smart City with IOT and Analytics, Journal of Neutrosophic and Fuzzy Systems, Vol. 1 , No. 1 , (2021) : 37-47 (Doi : https://doi.org/10.54216/JNFS.010104)

[7]  Mona Mohamed, A comparative study on Internet of Things (IoT):  Frameworks, Tools, Applications and Future directions, Journal of Intelligent Systems and Internet of Things, Vol. 1 , No. 1 , (2020) : 13-39 (Doi : https://doi.org/10.54216/JISIoT.010102)

[8]  Naomi  A.  Bajao,  &  Jae-an  Sarucam.  (2023).  Threats  Detection  in  the  Internet  of  Things  Using Convolutional  neural  networks,  long  short-term  memory,  and  gated  recurrent  units.  Mesopotamian Journal of CyberSecurity, 2023, 22–29. https://doi.org/10.58496/MJCS/2023/005.

[9]  Gopal Chaudhary , Smriti Srivastava , Manju Khari, Generative Edge Intelligence for Securing IoTassisted  Smart  Grid  against  Cyber-Threats,  International  Journal  of  Wireless  and  Ad  Hoc Communication, Vol. 6 , No. 1 , (2023) : 38-49 (Doi : https://doi.org/10.54216/IJWAC.060104).

[10]  Gao, J., Wang, H., & Shen, H. (2020). Task failure prediction in cloud data centers using deep learning. IEEE Transactions on Services Computing.

[11]  Obrenovic,  B.,  Du,  J.,  Godinic,  D.,  Tsoy,  D.,  Khan,  M.  A.  S.,  &  Jakhongirov,  I.  (2020). Sustaining  enterprise  operations  and  productivity  during  the  COVID-19  pandemic:  "Enterprise Effectiveness and Sustainability Model". Sustainability, 12(15), 5981.

[12]  Gao, J., Wang, H., & Shen, H. (2020, August). Machine learning based workload prediction in cloud  computing.  In 2020  29th  international  conference  on  computer  communications  and  networks (ICCCN) (pp. 1-9). IEEE.

[13]  Nwadigo,  O.,  Naismith,  N.  N.,  Ghaffarianhoseini,  A.,  Hoseini,  A.  G.,  & Tookey,  J.  (2020). Dynamic  Bayesian  network  modelling  for  predicting  adaptability  of  time  performance  during  time influencing factors disruptions in construction enterprise.  Engineering, Construction and Architectural Management.

[14]  Amudha,  G.  (2021).  Dilated  Transaction  Access  and  Retrieval:  Improving  the  Information Retrieval  of  Blockchain-Assimilated  Internet  of  Things  Transactions. Wireless  Personal Communications, 1-21.

[15]  Xin,  Q.,  Alazab,  M.,  Díaz,  V.G.,  Montenegro-Marin,  C.E.  and  Crespo,  R.G.,  2022.  A  deep learning architecture for power management in smart cities. Energy Reports, 8, pp.1568-1577.

[16]  Samiei, E., & Habibi, J. (2020). The mutual relation between Enterprise resource planning and knowledge management: A review. Global Journal of Flexible Systems Management, 21(1), 53-66.

[17]  Ramprasad, L., & Amudha, G. (2014, February). Spammer detection and tagging based user generated video search system—A survey. In International Conference on Information Communication and Embedded Systems (ICICES2014) (pp. 1-5). IEEE.

[18]  Han, Y., Deng,  Y., Cao, Z., & Lin, C. T. (2020). An interval-valued Pythagorean prioritized operator-based  game  theoretical  framework  with  its  applications  in  multicriteria  group  decision making. Neural Computing and Applications, 32(12), 7641-7659.

[19]  Ilmudeen, A.,  2022. Artificial Intelligence, Big Data Analytics and Big Data Processing for IoT-Based  Sensing  Data.  In Transforming  Management  with  AI,  Big-Data,  and  IoT (pp.  247-259). Cham: Springer International Publishing.

[20]  Challa, S., Das, A. K., Odelu, V., Kumar, N., Kumari, S., Khan, M. K., & Vasilakos, A. V. (2018).  An  efficient  ECC-based  provably  secure  three-factor  user  authentication  and  key  agreement protocol for wireless healthcare sensor networks. Computers & Electrical Engineering, 69, 534-554.

[21]  Beric, D., Havzi, S., Lolic, T., Simeunovic, N., & Stefanovic, D. (2020, March). Development of the MES software and Integration with an existing ERP Software in Industrial Enterprise. In  2020 19th International Symposium INFOTEH-JAHORINA (INFOTEH) (pp. 1-6). IEEE.

[22]  Darwish, A., Hassanien, A. E., Elhoseny, M., Sangaiah, A. K., & Muhammad, K. (2019). The impact  of  the  hybrid  platform  of  internet  of  things  and  cloud  computing  on  healthcare  systems: opportunities,  challenges,  and  open  problems.  Journal  of  Ambient  Intelligence  and  Humanized Computing, 10(10), 4151-4166.

[23]  Bzai, J., Alam, F., Dhafer, A., Bojović, M., Altowaijri, S.M., Niazi, I.K. and Mehmood, R., 2022.  Machine  Learning-Enabled  Internet  of  Things  (IoT):  Data,  Applications,  and  Industry Perspective. Electronics, 11(17), p.2676.

[24]  Huifeng,  W.,  Shankar,  A.,  &  Vivekananda,  G.  N.  (2020).  Modelling  and  simulation  of sprinters' health promotion strategy based on sports biomechanics. Connection Science, 1-19.

[25]  Huifeng, W., Kadry, S. N., & Raj, E. D. (2020). Continuous health monitoring of sportsperson using IoT devices based wearable technology. Computer Communications, 160, 588-595. 

[26]  Hnatenko, I., Orlova-Kurilova, O., Shtuler, I., Serzhanov, V., & Rubezhanska, V. (2020). An approach  to  innovation  potential  evaluation  as  a  means  of  enterprise  management 

improving. International Journal of Supply and Operations Management, 7(1), 112-118.

[27]  Tsvetkov,  V.  Y.,  Shaytura,  S.  V.,  &  Sultaeva,  N.  L.  (2020,  May).  Digital  enterprise management  in  cyberspace.  In 2nd  International  Scientific  and  Practical  Conference  "Modern Management  Trends  and  the  Digital  Economy:  from  Regional  Development  to  Global  Economic Growth" (MTDE 2020). Advances in Economics, Business and Management Research (Vol. 138, pp. 361-365).

[28]  Asaul,  A.  A.,  Voynarenko,  M.,  Yemchuk,  L.,  &  Dzhulii,  L.  (2020).  New  realities  of  the enterprise  management  system  information  support:  Economic  and  mathematical  models  and  cloud technologies. Journal of Information Technology Management, 12(3), 44-60.

[29]  Lee, A. H., Chen, S. C., &  Kang, H. Y. (2020). A decision-making framework for evaluating enterprise  resource  planning  systems  in  a  high-tech  industry. Quality  Technology  &  Quantitative Management, 17(3), 319-336.

[30]  Pérez-Castillo,  R.,  Ruiz,  F.,  &  Piattini,  M.  (2020).  A  decision-making  support  system  for Enterprise Architecture Modelling. Decision Support Systems, 131, 113249.

[31]  Nisar, Q. A., Nasir, N., Jamshed, S., Naz, S., Ali, M., & Ali, S. (2020). Big data management and  environmental  performance:  role  of  big  data  decision-making  capabilities  and  decision-making quality. Journal of Enterprise Information Management.

[32]  Popova, I. V. (2020, February). Management decision-making by the head of the peasant farm enterprise  under  conditions  of  uncertainty.  In IOP  Conference  Series:  Materials  Science  and Engineering (Vol. 753, No. 6, p. 062021). IOP Publishing.

[33]  Shan, S., Liu, X., Wei, Y., Xu, L., Zhang, B., & Yu, L. (2020). A new emergency management dynamic  value  assessment  model  based  on  social  media  data:  a  multiphase  decision-making perspective. Enterprise Information Systems, 14(5), 680-709.

[34]  Chandra, Y., Triana, R., Wang, G., & Legowo, N. (2020). Utilizing Big Data Framework to Support Decision Making Process: Enterprise Architecture Approach. International Journal, 9(3).

[35]  Sun, J., Wang, H.,  & Chen, J. (2020). Decision-Making of Port Enterprise Safety Investment Based on System Dynamics. Processes, 8(10), 1235.

[36]  Khudyakova,  T.,  Zhuravlyov,  V.,  Varkova,  N.,  Aliukov,  S.,  Shmidt,  S.,  &  Zhuravlyov,  N. (2020).  Improving  approaches  to  strategic  enterprise  management  in  the  context  of  sustainable development. Sustainability, 12(20), 8375.

[37]  Tytenko L. V., Bohdan S. V., Klyuchko O. O., Tymoshenko V. Yu. Software and information support for business analysis in enterprise management. Modern Economics. 2020. No. 20(2020). P. 272-277. DOI: https://doi.org/10.31521/modecon.V20(2020)-42.

Cite this Article as :
Style #
MLA Saif Saad Ahmed, Anwar Ja’afar M. Jawad, Shorook K. Abd, Aymen Mohammed, Amjed Hameed Majeed. "Intelligent Decision Making in IoT-Based Enterprise Management through Fusion Optimization with Deep Learning Models." Fusion: Practice and Applications, Vol. 11, No. 2, 2023 ,PP. 08-20 (Doi   :  https://doi.org/10.54216/FPA.110201)
APA Saif Saad Ahmed, Anwar Ja’afar M. Jawad, Shorook K. Abd, Aymen Mohammed, Amjed Hameed Majeed. (2023). Intelligent Decision Making in IoT-Based Enterprise Management through Fusion Optimization with Deep Learning Models. Journal of Fusion: Practice and Applications, 11 ( 2 ), 08-20 (Doi   :  https://doi.org/10.54216/FPA.110201)
Chicago Saif Saad Ahmed, Anwar Ja’afar M. Jawad, Shorook K. Abd, Aymen Mohammed, Amjed Hameed Majeed. "Intelligent Decision Making in IoT-Based Enterprise Management through Fusion Optimization with Deep Learning Models." Journal of Fusion: Practice and Applications, 11 no. 2 (2023): 08-20 (Doi   :  https://doi.org/10.54216/FPA.110201)
Harvard Saif Saad Ahmed, Anwar Ja’afar M. Jawad, Shorook K. Abd, Aymen Mohammed, Amjed Hameed Majeed. (2023). Intelligent Decision Making in IoT-Based Enterprise Management through Fusion Optimization with Deep Learning Models. Journal of Fusion: Practice and Applications, 11 ( 2 ), 08-20 (Doi   :  https://doi.org/10.54216/FPA.110201)
Vancouver Saif Saad Ahmed, Anwar Ja’afar M. Jawad, Shorook K. Abd, Aymen Mohammed, Amjed Hameed Majeed. Intelligent Decision Making in IoT-Based Enterprise Management through Fusion Optimization with Deep Learning Models. Journal of Fusion: Practice and Applications, (2023); 11 ( 2 ): 08-20 (Doi   :  https://doi.org/10.54216/FPA.110201)
IEEE Saif Saad Ahmed, Anwar Ja’afar M. Jawad, Shorook K. Abd, Aymen Mohammed, Amjed Hameed Majeed, Intelligent Decision Making in IoT-Based Enterprise Management through Fusion Optimization with Deep Learning Models, Journal of Fusion: Practice and Applications, Vol. 11 , No. 2 , (2023) : 08-20 (Doi   :  https://doi.org/10.54216/FPA.110201)
↑