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Data quality is a significant issue for any application that requests for analytics to support decision making. It becomes very important when we focus on Internet of Things (IoT) where numerous devices can interact to exchange and process…
The Medical Internet of Things, a recent technological advancement in medicine, is incredibly helpful in providing real-time monitoring of health metrics. This paper presents a non-invasive IoT system that tracks patients' emotions,…
Data from Internet of Things (IoT) sensors has emerged as a key contributor to decision-making processes in various domains. However, the quality of the data is crucial to the effectiveness of applications built on it, and assessment of the…
The fundamental aim of the healthcare sector is to incorporate different technologies to observe and keep a track of the various clinical parameters of the patients in day to day life. Distant patient observation applications are becoming…
The rapid growth of e-commerce has led to an overwhelming volume of customer feedback, from product reviews to service interactions. Extracting meaningful insights from this data is crucial for businesses aiming to improve customer…
The compliance of IoT platforms to quality is paramount to achieve users satisfaction. Currently, we do not have a comprehensive set of guidelines to appraise and select the most suitable IoT platform architectures that meet relevant…
One rapidly growing application of Internet of Things (IoT) is the protection of public health and well-being through enabling environmental monitoring services. In particular, an IoT-enabled health/accessibility monitoring service (HAMS)…
This study proposes a novel, integrative framework for patient-centered data science in the digital health era. We developed a multidimensional model that combines traditional clinical data with patient-reported outcomes, social…
In this work, we reflect on the data-driven modeling paradigm that is gaining ground in AI-driven automation of patient care. We argue that the repurposing of existing real-world patient datasets for machine learning may not always…
[Context and motivation] Internet of Things (IoT) is becoming common throughout everyday lives. However, the interaction is often different from when using e.g. computers and other smart devices. Furthermore, an IoT device is often…
The context-awareness of things that belong to IoT networks have to be considered in a distributed computation paradigm. In the paper we suggest the use of graph transformations and temporal logic as a formal framework for a knowledge…
Internet of Things (IoT) systems continuously collect a large amount of data from heterogeneous "smart objects" through standardised service interfaces. A key challenge is how to use these data and relevant event logs to construct…
Businesses have sought out new solutions to provide support and improve customer satisfaction as more products and services have become interconnected digitally. There is an inherent need for businesses to provide or outsource fast,…
The rapid deployment of Internet of Things (IoT) applications leads to massive data that need to be processed. These IoT applications have specific communication requirements on latency and bandwidth, and present new features on their…
Internet of Things (IoT) applications combine sensing, wireless communication, intelligence, and actuation, enabling the interaction among heterogeneous devices that collect and process considerable amounts of data. However, the…
We introduce the concept of adaptive trust in crowdsourced IoT services. It is a customized fine-grained trust tailored for specific IoT consumers. Usage patterns of IoT consumers are exploited to provide an accurate trust value for service…
Internet of Things Driven Data Analytics (IoT-DA) has the potential to excel data-driven operationalisation of smart environments. However, limited research exists on how IoT-DA applications are designed, implemented, operationalised, and…
Machine learning can analyze vast amounts of data generated by IoT devices to identify patterns, make predictions, and enable real-time decision-making. By processing sensor data, machine learning models can optimize processes, improve…
Internet of Things (IoT) and cloud computing together give us the ability to sense, collect, process, and analyse data so we can use them to better understand behaviours, habits, preferences and life patterns of users and lead them to…
Automation and computer intelligence to support complex human decisions becomes essential to manage large and distributed systems in the Cloud and IoT era. Understanding the root cause of an observed symptom in a complex system has been a…