Vendor Highlights – IoT, AI, and Process Mining
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V4I4P115Keywords:
IoT, Artificial Intelligence, Process Mining, Vendor Analysis, Digital Transformation, Industry 4.0, Intelligent Automation, Business Process Optimization, Data Analytics, Emerging TechnologiesAbstract
The rapid advancement of digital technology is transforming their company operations, competition & innovation, with the confluence of the Internet of Things (IoT), Artificial Intelligence (AI) & process mining emerging as a highly disruptive trend in the contemporary business landscape. The Internet of Things (IoT) is providing actual time insights into assets, operations & consumer behaviors, whilst Artificial Intelligence (AI) is enhancing intelligence, automation, and predictive functionalities that are beyond many conventional analytics. Process mining enables firms to acquire a data-driven comprehension of these processes, inefficiencies & improve their possibilities on a huge scale. Collectively, these areas are establishing new pathways for digital transformation by enabling organizations to transition from reactive decision-making to proactive and predictive frameworks. Prominent companies are not only providing their specialized solutions but are also progressively establishing their comprehensive platforms that integrate IoT connection, AI-driven insights & process mining tools to achieve these quantifiable business results. This essay emphasizes how manufacturers are maneuvering through these rapidly evolving sectors, their distinctive strategies for market distinctiveness & the potential for interoperability within these ecosystems. Key results highlight the increasing integration of IoT, AI, and process mining as organizations want these comprehensive solutions that enhance operational efficiency & foster strategic innovation. This article provides an overview of vendor strategies & their alignment with corporate requirements, intending to provide business executives, IT practitioners & these decision-makers with practical insights for assessing solutions and formulating adoption roadmaps
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References
[1] Reinkemeyer, Lars. "Process mining in action." Process mining in action principles, use cases and outloook 11.7 (2020): 116-128.
[2] Reinkemeyer, Lars. "Status and future of process mining: from process discovery to process execution." Process Mining Handbook. Cham: Springer International Publishing, 2022. 405-415.
[3] Shaik, Babulal. "Automating Compliance in Amazon EKS Clusters With Custom Policies." Journal of Artificial Intelligence Research and Applications 1.1 (2021): 587-10.
[4] Patel, Piyushkumar. "Robotic Process Automation (RPA) in Tax Compliance: Enhancing Efficiency in Preparing and Filing Tax Returns." African Journal of Artificial Intelligence and Sustainable Development 2.2 (2022): 441-66.
[5] Jacobi, Christoph, et al. "Maturity model for applying process mining in supply chains: Literature overview and practical implications." Logistics Journal: Proceedings 16 (2020).
[6] Katangoori, Sivadeep, and Anudeep Katangoori. “Intelligent ETL Orchestration With Reinforcement Learning and Bayesian Optimization”. American Journal of Data Science and Artificial Intelligence Innovations, vol. 3, Oct. 2023, pp. 458-8
[7] Allam, Hitesh. "Security-Driven Pipelines: Embedding DevSecOps into CI/CD Workflows." International Journal of Emerging Trends in Computer Science and Information Technology 3.1 (2022): 86-97.
[8] Singh, Prasannjeet, et al. "Using log analytics and process mining to enable self-healing in the Internet of Things." Environment Systems and Decisions 42.2 (2022): 234-250.
[9] Datla, Lalith Sriram. “Infrastructure That Scales Itself: How We Used DevOps to Support Rapid Growth in Insurance Products for Schools and Hospitals”. International Journal of AI, BigData, Computational and Management Studies, vol. 3, no. 1, Mar. 2022, pp. 56-65
[10] Van der Aalst, Wil MP, and Anton JMM Weijters. "Process mining: a research agenda." Computers in industry 53.3 (2004): 231-244.
[11] Burattin, Andrea. "Process mining techniques in business environments." Lecture Notes in Business Information Processing 207.1 (2015): 220.
[12] Guntupalli, Bhavitha. “Exception Handling in Large-Scale ETL Systems: Best Practices”. International Journal of AI, BigData, Computational and Management Studies, vol. 3, no. 4, Dec. 2022, pp. 28-36
[13] Seeliger, Alexander, Timo Nolle, and Max Mühlhäuser. "Process explorer: an interactive visual recommendation system for process mining." KDD Workshop on Interactive Data Exploration and Analytics. 2018.
[14] Katangoori, Sivadeep, and Sushil Deore. “Lakehouse Architecture and the Semantic Revolution: Bridging Analytics and Governance With AI”. The Distributed Learning and Broad Applications in Scientific Research, vol. 8, Sept. 2022, pp. 275-00
[15] Shaik, Babulal, and Jayaram Immaneni. "Enhanced Logging and Monitoring With Custom Metrics in Kubernetes." African Journal of Artificial Intelligence and Sustainable Development 1 (2021): 307-30.
[16] Balkishan Arugula. “Knowledge Graphs in Banking: Enhancing Compliance, Risk Management, and Customer Insights”. European Journal of Quantum Computing and Intelligent Agents, vol. 6, Apr. 2022, pp. 28-55
[17] 17. Tien, James M. "Internet of things, real-time decision making, and artificial intelligence." Annals of Data Science 4.2 (2017): 149-178.
[18] Patel, Piyushkumar. "Navigating the BEAT (Base Erosion and Anti-Abuse Tax) under the TCJA: The Impact on Multinationals’ Tax Strategies." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 342-6.
[19] Sinnott, Richard O., et al. "The Australian Digital Observatory: Social Media Collection, Discovery and Analytics at Scale." International Conference on Big Data Intelligence and Computing. Singapore: Springer Nature Singapore, 2022.
[20] Allam, Hitesh. "Bridging the Gap: Integrating DevOps Culture into Traditional IT Structures." International Journal of Emerging Trends in Computer Science and Information Technology 3.1 (2022): 75-85.
[21] Szelągowski, Marek. Dynamic business process management in the knowledge economy: Creating value from intellectual capital. Vol. 71. Springer, 2019.
[22] Katangoori, Sivadeep, and Sushil Deore. “Edge-Cloud Hybrid Data Pipelines: Architectures for Federated Analytics and Learning”. The Distributed Learning and Broad Applications in Scientific Research, vol. 8, May 2022, pp. 215-46
[23] Guntupalli, Bhavitha, and Venkata ch. “How I Optimized a Legacy Codebase With Refactoring Techniques”. International Journal of Emerging Trends in Computer Science and Information Technology, vol. 3, no. 1, Mar. 2022, pp. 98-106
[24] Datla, Lalith Sriram. “Proactive Application Monitoring for Insurance Platforms: How AppDynamics Improved Our Response Times”. International Journal of Emerging Research in Engineering and Technology, vol. 4, no. 1, Mar. 2023, pp. 54-65
[25] Wamba-Taguimdje, Serge-Lopez, et al. "Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects." Business process management journal 26.7 (2020): 1893-1924.
[26] Patel, Piyushkumar. "The Corporate Transparency Act: Implications for Financial Reporting and Beneficial Ownership Disclosure." Journal of Artificial Intelligence Research and Applications 2.1 (2022): 489-08.
[27] Arugula, Balkishan, and Pavan Perala. “Building High-Performance Teams in Cross-Cultural Environments”. International Journal of Emerging Research in Engineering and Technology, vol. 3, no. 4, Dec. 2022, pp. 23-31
[28] Li, Rongpeng, et al. "Intelligent 5G: When cellular networks meet artificial intelligence." IEEE Wireless communications 24.5 (2017): 175-183.
[29] Shaik, Babulal. "Automating Zero-Downtime Deployments in Kubernetes on Amazon EKS." Journal of AI-Assisted Scientific Discovery 1.2 (2021): 355-77.
[30] Smith, Reid G., and Adam Farquhar. "The road ahead for knowledge management: an AI perspective." AI magazine 21.4 (2000): 17-17.
[31] Datla, Lalith Sriram. “Postmortem Culture in Practice: What Production Incidents Taught Us about Reliability in Insurance Tech”. International Journal of Emerging Research in Engineering and Technology, vol. 3, no. 3, Oct. 2022, pp. 40-49
[32] Li, Qi, Abdul Mohammad, and Luca Morandini. "The Australian Digital Observatory: Social Media Collection, Discovery and Analytics." Big Data Intelligence and Computing: International Conference, DataCom 2022, Denarau Island, Fiji, December 8–10, 2022, Proceedings. Vol. 13864. Springer Nature, 2023.
[33] Jani, Parth. "Real-Time Streaming AI in Claims Adjudication for High-Volume TPA Workloads." International Journal of Artificial Intelligence, Data Science, and Machine Learning 4.3 (2023): 41-49.
[34] Bécue, Adrien, Isabel Praça, and João Gama. "Artificial intelligence, cyber-threats and Industry 4.0: Challenges and opportunities." Artificial intelligence review 54.5 (2021): 3849-3886.
[35] Guntupalli, Bhavitha. “Asynchronous Programming in Java Python: A Developer’s Guide”. International Journal of Emerging Research in Engineering and Technology, vol. 3, no. 2, June 2022, pp. 70-78
[36] Bernstein, Abraham, Foster Provost, and Shawndra Hill. "Toward intelligent assistance for a data mining process: An ontology-based approach for cost-sensitive classification." IEEE Transactions on knowledge and data engineering 17.4 (2005): 503-518.
[37] Beverungen, Daniel, et al. "Seven paradoxes of business process management in a hyper-connected world." Business & Information Systems Engineering (BISE)(früher: Wirtschaftsinformatik WI) 63.63 (2020): 145-156.
