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Thanks to the rapid growth in wearable technologies and recent advancement in machine learning and signal processing, monitoring complex human contexts becomes feasible, paving the way to develop human-in-the-loop IoT systems that naturally…

Enabling full robotic workloads with diverse behaviors on mobile systems with stringent resource and energy constraints remains a challenge. In recent years, attempts have been made to deploy single-accelerator-based computing platforms…

Humanoid robots derive much of their dexterity from hyper-dexterous whole-body movements, enabling tasks that require a large operational workspace: such as picking objects off the ground. However, achieving these capabilities on real…

Programming a robot to deal with open-ended tasks remains a challenge, in particular if the robot has to manipulate objects. Launching, grasping, pushing or any other object interaction can be simulated but the corresponding models are not…

The next generation of machine learning systems must be adept at perceiving and interacting with the physical world through a diverse array of sensory channels. Commonly referred to as the `Internet of Things (IoT)' ecosystem, sensory data…

In an increasingly automated world -- from warehouse robots to self-driving cars -- streamlining the development and deployment process and operations of robotic applications becomes ever more important. Automated DevOps processes and…

This research empirically examines embedded development tools viable for on-device TinyML implementation. The research evaluates various development tools with various abstraction levels on resource-constrained IoT devices, from basic…

The increasing demand for fast and cost effective last mile delivery solutions has catalyzed significant advancements in drone based logistics. This research describes the development of an AI integrated drone delivery system, focusing on…

Location-Based Service (LBS) is rapidly becoming the next ubiquitous technology for a wide range of mobile applications. To support applications that demand nearest-neighbor and history queries, an LBS spatial indexer must be able to…

Physical AI is experiencing rapid growth with frontier foundation models increasing its capabilities across general environments. Physical AI tasks are characterized by inference properties that are markedly different from digital AI. They…

Energy harvesting offers an attractive and promising mechanism to power low-energy devices. However, it alone is insufficient to enable an energy-neutral operation, which can eliminate tedious battery charging and replacement requirements.…

The Adaptable TeaStore has recently been proposed as a reference model for adaptable microservice architectures. It includes different configurations, as well as scenarios requiring to transition between them. We describe an implementation…

Next-generation Multiple-Input Multiple-Output (MIMO) is expected to be intelligent and scalable. In this paper, we study Large Language Model (LLM)-enabled next-generation MIMO networks. Firstly, we provide an overview of the development,…

The present study introduces an Android based application that focuses on promoting students' learning experience when interacting with Lego Mindstorms Robotic Kit NXT. A thorough investigation of the current literature reveals that there…

We present a tool that leverages generative AI to accelerate the migration of on-premises applications to the cloud. The Cloud Migration LLM accepts input from the user specifying the parameters of their migration, and outputs a migration…

As autonomous driving systems being deployed to millions of vehicles, there is a pressing need of improving the system's scalability, safety and reducing the engineering cost. A realistic, scalable, and practical simulator of the driving…

Due to the multidisciplinary nature of wearable technology, the industry faces potential limitations in innovation. The wearable technology industry is still in its infancy and increased applicable use faces stagnation despite the plethora…

This work discusses the benefits of having multiple simulated environments with different degrees of realism for the development of algorithms in scenarios populated by autonomous nodes capable of communication and mobility. This approach…

The integration of Artificial Intelligence (AI) into IT Operations Management (ITOM), commonly referred to as AIOps, offers substantial potential for automating workflows, enhancing efficiency, and supporting informed decision-making.…

We use a duoethnographic approach to study how wearable-integrated LLM chatbots can assist with personalized stress management, addressing the growing need for immediacy and tailored interventions. Two researchers interacted with custom…