Eghe Ikponmwosa-Eweka | Artificia Intelligence Developer
Teeside University
Eghe Ikponmwosa-Eweka is an Artificial Intelligence Developer affiliated with Teesside University and Scott Bros, specializing in the design of end-to-end digital systems for environmental and industrial applications. With a background in Chemical Engineering and a master’s degree in Applied Artificial Intelligence and Data Analytics, she bridges industrial process expertise with advanced AI-driven analytics. Eghe previously worked as a Research Data Analyst within the NHS, where she supported data-driven decision-making in highly regulated healthcare environments. Her work focuses on building scalable digital pipelines that integrate remote data collection, secure cloud infrastructure, and intelligent automation to enhance data quality, traceability, and analytical insight. Her interests centre on digital transformation, data standards, and deploying AI solutions to support sustainability and operational efficiency.
Appearances:
Day 2: 7th May @ 13:40
From Remote Data Collection to Cloud Analytics: Building End-to-End Digital Pipelines for Environmental Laboratories
Environmental monitoring increasingly depends on IoT-enabled sensor systems that generate continuous streams of field data. This session presents a practical case study demonstrating how environmental data can be collected using IoT sensors, securely transmitted to cloud infrastructure, and transformed through analytics and visualisation. Drawing on applied research and industry collaboration, I will outline the architecture of the digital pipeline, including data ingestion, storage, processing, and analytical modelling. The session will highlight key considerations in data standardisation, system integration, and scalability. Attendees will gain insight into designing efficient cloud-based frameworks that convert raw sensor data into actionable intelligence for environmental monitoring and laboratory decision-making.
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