Machine-to-infrastructure middleware platform for data management in IoT

Richard K. Lomotey, Sumanth Sriramoju, Rita Orji

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The emergent usage of network-based consumer devices has created an ecosystem for heterogeneous ‘aware’ and interconnected devices with unique IDs interacting with other machines/objects, infrastructure, and nature. This is called the internet of things (IoT), and it is inspired by smart devices with sensing and connectivity capability that can aid with data collection. While the data from sensors can give insightful enterprise information through analytics, it is needful to first and foremost create the IoT framework with automation support for machine-to-infrastructure (M2I) communication. However, there are only few research works that focus on enabling M2I communication though many studies are dedicated to machine-to-machine (M2M) communication. Key challenges in the IoT infrastructure design are multiple device semantics and protocol variations which can limit interoperability. This work proposes a middleware with both M2I and M2M capabilities which addresses these problems based on mapping techniques between the heterogeneous device semantics and providing a common interface for data exchanges via varied protocols. When a device is discoverable, our middleware uses enhanced environment-context ontology to match the appropriate communication protocol. This aids with pushing data from within-range sensors to a cloud-hosted infrastructure. The extensive experiments conducted on the proposed system show superiority over similar services.

Original languageEnglish (US)
Pages (from-to)90-106
Number of pages17
JournalInternational Journal of Business Process Integration and Management
Issue number2
StatePublished - 2019

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Strategy and Management
  • Management Science and Operations Research


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