*** Hybrid event ***

Room TG23, Town Hall ground floor (although a link to a Zoom meeting is provided at the end of this announcement* we strongly encourage everyone to attend in person)

Speaker: Adetunji Ademola (PGR Computer Science)

Title of talk: “Investigating the interoperability of Electronic Health Records and associated privacy and security issues”

Bio of Speaker: As an accomplished IT professional with over a decade of experience and currently a final-year researcher, I am deeply committed to delivering exceptional customer service and have honed my communication skills to an advanced level. Renowned for my adept problem-solving abilities, I thrive in dynamic environments and adapt seamlessly to new challenges. Possessing a proactive and innovative mindset, I approach every task with enthusiasm and am eager to tackle complex projects that allow for further skill development and organizational contribution. My expertise encompasses a wide array of operating systems, including Windows 10 and 11 as well as Mac OS. I boast a comprehensive understanding of Microsoft Office programs and cloud services, with proficiency in Office Suite, Exchange, Office 365, Azure, SharePoint, Teams, OneDrive, and 365 admin center administration. Additionally, I am well-versed in agile methodologies and remote support techniques, with a keen eye for system monitoring and optimization.

Abstract: This research tackles the crucial obstacles hindering both technical and semantic interoperability in electronic health record (EHR) systems, pivotal for smooth data exchange and integration across diverse healthcare environments and platforms. The proposed TASSIPS framework, capitalizes on cutting-edge technologies such as vector databases, encryption, intrusion detection mechanisms, and artificial intelligence (AI) to facilitate the seamless translation and alignment of medical terminologies. By amalgamating these technologies within the TASSIPS framework, the research ensures the preservation of semantic integrity in clinical data exchange across disparate EHR platforms, while prioritizing patient data security and privacy. Departing from conventional methods reliant on manual ontology development, TASSIPS harnesses the robust capabilities of vector databases to capture intricate semantic relationships inherent in medical concepts. Furthermore, AI algorithms are deployed to enrich the vector representations and automate the mapping process, fostering more streamlined and accurate semantic translation. The efficacy of the framework is substantiated through the creation of two prototype EHR systems interconnected via a central interoperability platform. Rigorous evaluation of the framework encompasses comprehensive testing of its semantic interoperability, usability, and performance, with valuable input from healthcare professionals driving iterative enhancements. By facilitating interoperability at the semantic level, this research significantly advances healthcare information exchange, ultimately enhancing patient care and clinical decision-making.

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Speaker: Faryal Batool (PGR Computer Science)

Title of talk: "Climate Change: Combating Deforestation Using WSN and AI Techniques"

Bio of Speaker: I completed my Bachelor's in IT and pursued my Master's in Computer Science, both in Pakistan. My hometown is Quetta, where I received my early education, and I later moved to Lahore for my Master's degree. I worked as a lecturer at Lahore Garrison University for four years before deciding to embark on my Ph.D. journey at Middlesex University. Apart from my academic pursuits, I have been actively engaged in extracurricular activities. These experiences have enriched my overall understanding and contributed to my personal and professional growth.

Abstract: Given that climate change is already happening in the modern world, there is a large list of human-made activities that have contributed to various climate change issues both now and in the future. These worries are made worse by deforestation, which significantly contributes to climate change. It amplifies the consequences of climate change by releasing enormous amounts of stored carbon into the atmosphere as well as upsetting ecosystems. This research will explore the creative application of Wireless Sensor Networks (WSN) and Artificial Intelligence (AI) technology to the combat against deforestation. To monitor the environment in real-time, WSN deployment in forested areas is crucial. Forests contain a variety of sensor equipment, such as temperature sensors, humidity sensors, smoke alarms, soil moisture monitors, and pH sensors. These sensors gather vital information about the forest ecosystem, which is the cornerstone of our strategy. The early detection of anomalies that could indicate natural disasters like droughts or floods is made possible with the help of temperature and humidity sensors, which offer insights into microclimate conditions. AI systems examine WSN data to forecast and address natural disasters including floods, droughts, and heavy rain. Machine learning algorithms can predict hazardous weather conditions and issue early warnings, enabling prompt resource allocation and evacuation.

This research contributes to a comprehensive and technologically cutting-edge strategy to combat deforestation, alleviate the effects of climate change, and promote the sustainable preservation of important forest ecosystems by integrating WSN and AI within these three areas. The use of wireless sensor networks (WSNs) combined with artificial intelligence (AI) is suggested as a solution to these complex problems. Real-time monitoring of weather, tree health, and human activity is made possible by WSNs, which are furnished with environmental sensors, cameras, and AI algorithms. This technology provides data for sustainable forest management, reforestation, and interventions to counter environmental risks, as well as early warning systems, evidence for law enforcement against illegal logging, and other purposes. We may improve our capacity to safeguard and preserve trees, and essential elements of the world's ecosystems, and lessen the negative effects of climate change by utilizing WSNs and AI across multiple dimensions. This thesis primarily focuses on three key domains that have a significant influence on deforestation: unauthorised human activities occurring within specific forest regions, the effects of weather conditions on deforestation patterns, and the consequences of natural disasters on the health of trees. The suggested approach will involve applying the use of artificial intelligence (AI) methodologies working together with Wireless Sensor Network (WSN) technologies to address and mitigate the aforementioned challenges.

(*) Join Zoom Meeting

https://mdx-ac-uk.zoom.us/j/94189623517?pwd=SVU1YVB6T2VON3VqenJqdzNmc0V0UT09

Meeting ID: 941 8962 3517

Passcode: 383393