Design of a wearable platform for PPG analysis with multicore low-power processor

Photoplethysmography (PPG) sensors allow for noninvasive and comfortable heart-rate (HR) monitoring, suitable for compact wearable devices. However, PPG signals collected from such devices often suffer from corruption caused by motion artifacts. This is typically addressed by combining the PPG signal with acceleration measurements from an inertial sensor. Recently, different energy-efficient deep learning approaches for heart rate estimation have been proposed. To test these new solutions, in this work, we developed a highly wearable platform (42mm x 48 mm x 1.2mm) for PPG signal acquisition and processing, based on GAP9, a parallel ultra low power system-on-chip featuring nine cores RISC-V compute cluster with neural network accelerator and 1 core RISC-V controller. The hardware platform also integrates a commercial complete Optical Biosensing Module and an ARM-Cortex M4 microcontroller unit (MCU) with Bluetooth low-energy connectivity. To demonstrate the capabilities of the system, a deep learning-based approach for PPG-based HR estimation has been deployed. Thanks to the reduced power consumption of the digital computational platform, the total power budget is just 2.67 mW providing up to 5 days of operation (105 mAh battery).

Mac protocols for linear wireless (sensor) networks

Wireless sensor networks (WSNs) consist of a large number of sensor nodes, characterized by low power constraint, limited transmission range and limited computational capabilities [1][2].The cost of these devices is constantly decreasing, making it possible to use a large number of sensor devices in a wide array of commercial, environmental, military, and healthcare fields. Some of these applications involve placing the sensors evenly spaced on a straight line for example in roads, bridges, tunnels, water catchments and water pipelines, city drainages, oil and gas pipelines etc., making a special class of these networks which we define as a Linear Wireless Network (LWN). In LWNs, data transmission happens hop by hop from the source to the destination, through a route composed of multiple relays. The peculiarity of the topology of LWNs, motivates the design of specialized protocols, taking advantage of the linearity of such networks, in order to increase reliability, communication efficiency, energy savings, network lifetime and to minimize the end-to-end delay [3]. In this thesis a novel contention based Medium Access Control (MAC) protocol called L-CSMA, specifically devised for LWNs is presented. The basic idea of L-CSMA is to assign different priorities to nodes based on their position along the line. The priority is assigned in terms of sensing duration, whereby nodes closer to the destination are assigned shorter sensing time compared to the rest of the nodes and hence higher priority. This mechanism speeds up the transmission of packets which are already in the path, making transmission flow more efficient. Using NS-3 simulator, the performance of L-CSMA in terms of packets success rate, that is, the percentage of packets that reach destination, and throughput are compared with that of IEEE 802.15.4 MAC protocol, de-facto standard for wireless sensor networks. In general, L-CSMA outperforms the IEEE 802.15.4 MAC protocol.

Simulation of visible light communications in vehicular networks

The rapid development in the field of lighting and illumination allows low energy consumption and a rapid growth in the use, and development of solid-state sources. As the efficiency of these devices increases and their cost decreases there are predictions that they will become the dominant source for general illumination in the short term. The objective of this thesis is to study, through extensive simulations in realistic scenarios, the feasibility and exploitation of visible light communication (VLC) for vehicular ad hoc networks (VANETs) applications. A brief introduction will introduce the new scenario of smart cities in which visible light communication will become a fundamental enabling technology for the future communication systems. Specifically, this thesis focus on the acquisition of several, frequent, and small data packets from vehicles, exploited as sensors of the environment. The use of vehicles as sensors is a new paradigm to enable an efficient environment monitoring and an improved traffic management. In most cases, the sensed information must be collected at a remote control centre and one of the most challenging aspects is the uplink acquisition of data from vehicles. My thesis discusses the opportunity to take advantage of short range vehicle-to-vehicle (V2V) and vehicle-to-roadside (V2R) communications to offload the cellular networks. More specifically, it discusses the system design and assesses the obtainable cellular resource saving, by considering the impact of the percentage of vehicles equipped with short range communication devices, of the number of deployed road side units, and of the adopted routing protocol. When short range communications are concerned, WAVE/IEEE 802.11p is considered as standard for VANETs. Its use together with VLC will be considered in urban vehicular scenarios to let vehicles communicate without involving the cellular network. The study is conducted by simulation, considering both a simulation platform (SHINE, simulation platform for heterogeneous interworking networks) developed within the Wireless communication Laboratory (Wilab) of the University of Bologna and CNR, and network simulator (NS3). trying to realistically represent all the wireless network communication aspects. Specifically, simulation of vehicular system was performed and introduced in ns-3, creating a new module for the simulator. This module will help to study VLC applications in VANETs. Final observations would enhance and encourage potential research in the area and optimize performance of VLC systems applications in the future.

Study of a new method for high energy top tagging at the ATLAS experiment

Since its discovery, top quark has represented one of the most investigated field in particle physics. The aim of this thesis is the reconstruction of hadronic top with high transverse momentum (boosted) with the Template Overlap Method (TOM). Because of the high energy, the decay products of boosted tops are partially or totally overlapped and thus they are contained in a single large radius jet (fat-jet). TOM compares the internal energy distributions of the candidate fat-jet to a sample of tops obtained by a MC simulation (template). The algorithm is based on the definition of an overlap function, which quantifies the level of agreement between the fat-jet and the template, allowing an efficient discrimination of signal from the background contributions. A working point has been decided in order to obtain a signal efficiency close to 90% and a corresponding background rejection at 70%. TOM performances have been tested on MC samples in the muon channel and compared with the previous methods present in literature. All the methods will be merged in a multivariate analysis to give a global top tagging which will be included in ttbar production differential cross section performed on the data acquired in 2012 at sqrt(s)=8 TeV in high phase space region, where new physics processes could be possible. Due to its peculiarity to increase the pT, the Template Overlap Method will play a crucial role in the next data taking at sqrt(s)=13 TeV, where the almost totality of the tops will be produced at high energy, making the standard reconstruction methods inefficient.