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Localization in urban environments is becoming increasingly important and used in tools such as ARCore [11], ARKit [27] and others. One popular mechanism to achieve accurate indoor localization as well as a map of the space is using Visual Simultaneous ...

In recent years, considerable effort has been recently exerted to explore the high-precision RF-tracking systems indoors to satisfy various real-world demands. However, such systems are tailored for a particular type of device (e.g., RFID, WSN or Wi-Fi)...

This paper introduces the concept of Neural Weight Virtualization - which enables fast and scalable in-memory multitask deep learning on memory-constrained embedded systems. The goal of neural weight virtualization is two-fold: (1) packing multiple DNNs ...

We present DarkneTZ, a framework that uses an edge device's Trusted Execution Environment (TEE) in conjunction with model partitioning to limit the attack surface against Deep Neural Networks (DNNs). Increasingly, edge devices (smartphones and consumer ...

Machine learning, particularly deep learning, is being increasing utilised in space applications, mirroring the groundbreaking success in many earthbound problems. Deploying a space device, e.g. a satellite, is becoming more accessible to small actors ...

Compression methods for deep learning have been recently used to port deep neural networks into resource-constrained devices - such as digital gloves and smartwatches - for human activity recognition (HAR). While the results have been in favor of ...

3D maps of urban environments are useful in various fields ranging from cellular network planning to urban planning and climatology. These models are typically constructed using expensive techniques such as manual annotation with 3D modeling tools, ...

In recent years, convolutional networks have demonstrated unprecedented performance in the image restoration task of super-resolution (SR). SR entails the upscaling of a single low-resolution image in order to meet application-specific image quality ...

IoT and deep learning based computer vision together create an immense market opportunity, but running deep neural networks (DNNs) on resource-constrained IoT devices remains challenging. Offloading DNN inference to an edge server is a promising ...

Smart speakers allow users to interact with home appliances using voice commands and are becoming increasingly popular. While voice-based interface is intuitive, it is insufficient in many scenarios, such as in noisy or quiet environments, for users ...

The virtualization of radio access networks (vRAN) is the last milestone in the NFV revolution. However, the complex dependencies between computing and radio resources make vRAN resource control particularly daunting. We present vrAIn, a dynamic ...

Sign language is a natural and fully-formed communication method for deaf or hearing-impaired people. Unfortunately, most of the state-of-the-art sign recognition technologies are limited by either high energy consumption or expensive device costs and ...

This poster demonstrates a mood forecasting system that forecasts tomorrow's mood based on today's data collected from SNS and smartphone sensors. Forecasting user's mood plays an important role in diverse topics such as recommendation systems. We ...

Travelling is not always fun for wheelchair users in the built environment (both indoor and outdoor) in presence of various unknown barriers, such as, uneven sidewalks, curb heights, stairs, ramps, cobbled streets, etc. Also, elderly individuals are ...

Modern edge devices such as smartphones, tablets, smart glasses, VR and AR headsets have gotten more capable with high-resolution displays, powerful CPU/GPUs, multiple sensing modalities and multiple connectivity options. These platform capabilities are ...

Real-time traffic monitoring has had widespread success via crowd-sourced GPS data. While drivers benefit from this low-level, low-latency road information, any high-level traffic data such as road closures and accidents currently have very high latency ...

This paper investigates the use of drones for live inspection in the construction industry. The key technical challenge is the real-time registration of the drone video feed to the architectural plan. We present and evaluate three different approaches ...

Artificial Intelligence (AI) and Machine Learning (ML) approaches, well known from IT disciplines, are beginning to excite the networking and networked systems community. Of late, we are seeing a huge excitement about applying AI and ML to networked ...

Mobile vision systems such as smartphones, drones, and augmented-reality headsets are revolutionizing our lives. These systems usually run multiple applications concurrently and their available resources at runtime are dynamic due to events such as ...

The widespread availability of Internet-of-Thing (IoT) devices, wearable sensors and smart watches have been promoting innovative activity recognition applications in our everyday lives. Recognizing dance steps with fine granularity using wearables is ...