Introduction

Jarrett, Daniel; Habets, Emanuël A. P.; Naylor, Patrick A.

doi:10.1007/978-3-319-42211-4_1

Cited by 3 publications

(1 citation statement)

References 41 publications

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“…One popular beamformer is based on a Plane-wave Decomposition (PWD) approach, whereby spherical harmonics for certain directions on the sphere are used as the beamforming weights [20,21]. However, this approach is inherently limited by the spatial resolution of the input signals, which can often be insufficient at lower orders and result in blurred activity maps.…”

Section: Sound-field Visualization In the Shdmentioning

confidence: 99%

Applications of Spatially Localized Active-Intensity Vectors for Sound-Field visualization

McCormack¹,

Delikaris-Manias²,

Politis³

et al. 2019

J. Audio Eng. Soc.

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The purpose of this article is to detail and evaluate three alternative approaches to soundfield visualization, which all employ the use of spatially localized active-intensity (SLAI) vectors. These SLAI vectors are of particular interest, as they allow direction-of-arrival (DoA) estimates to be extracted in multiple spatially localized sectors, such that a sound source present in one sector has reduced influence on the DoA estimate made in another sector. These DoA estimates may be used to visualize the sound-field by either: (I) directly depicting the estimates as icons, with their relative size dictated by the corresponding energy of each sector; (II) generating traditional activity maps via histogram analysis of the DoA estimates; or (III) by using the DoA estimates to reassign energy and subsequently sharpen traditional beamformer-based activity maps. Since the SLAI-based DoA estimates are continuous, these approaches are inherently computationally efficient, as they forego the need for dense scanning grids to attain high-resolution imaging. Simulation results also show that these SLAI-based alternatives outperform traditional active-intensity and beamformer-based approaches, for the majority of cases.

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Section: Sound-field Visualization In the Shdmentioning

confidence: 99%

Applications of Spatially Localized Active-Intensity Vectors for Sound-Field visualization

McCormack¹,

Delikaris-Manias²,

Politis³

et al. 2019

J. Audio Eng. Soc.

View full text Add to dashboard Cite

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A Novel Design and Implementation of Imaging Chip Using AXI Protocol for MPSOC on FPGA

Archana¹,

Patel²

2018

Intelligent Systems in Cybernetics and Automation Control Theory

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Biometric Security and Internet of Things (IoT)

Obaidat

Rana

Maitra

et al. 2018

Biometric-Based Physical and Cybersecurity Systems

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The human-to-machine and human-to-human communications are transforming to machine-to-machine communications by which several decision-making systems can be built. When different Internet enabled smart devices interact with each other's to achieve a goal (application depended), then a network is formed in which different sophisticated technologies will integrate to each other to form Internet of Things (IoT). It encompasses the vast amount of diverse smart devices, which collaborate with each other to achieve different smart applications like, smart cities, connected cars, automated agriculture and so on. Though Radio Frequency Identification (RFID), Wireless, mobile and sensor technologies make IoT feasible, but it suffers from many challenges like scalability, security, and heterogeneity problems. Out of many challenges, security is one of the primary concerns in IoT. Without proper security and privacy, the business model of IoT will not succeed. This chapter discusses the secure solutions for IoT using biometric features of users as well as end users. The chapter will demonstrate that biometric security is most feasible, reliable and efficient with respect to other existing security arrangements.process is controlled to ensure quality of product by getting different parameter values from sensors [1], [2].IBM has launched Smart Home solution [7], better known as "Stratecast" to provide services to users allowing seamless communication among various smart devices in house, like medical devices, computers, mobiles, TVs, lighting, security and sound system. IBM is collaborating with Verizon as a communication service provider (CSP) and Philips as a device vendor to implement the architecture. Siemens, Cisco, Xerox, Microsoft, MIT and many others are working in this domain. They have set nearly 20 home labs using more than 30 home appliances, five network protocols and three Artificial Intelligence (AI) techniques [8]. The Intel smart home platform supports recognition of family members by voice or face and personalizes the home. Intel provides IoT solutions for smarter building to support personalization by controlling over the office/living environment, mobility by enabling managers to monitor property remotely, and sustainability and efficiency in terms of saving energy, water and other building resources.Healthcare: Another impact area is healthcare [9], [10], where IoT can be used in tracking of people (i.e., patients and staff) or objects, recognition and verification of people, and automatic data collection [11]. Real-time tracking of person or objects in motion, in the case of patient-flow monitoring helps to manage staffing and improve the workflow in hospitals. Identification and authentication of staff secure the patients and help to avoid mistakes like wrong drug/dose/time. Automatic collection of clinical data must be enabled to enrich medical inventory. Real-time monitoring of patients is possible by attaching different sensors to measure body temperature, blood pressure, and heart response. These Io...

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Introduction

Cited by 3 publications

References 41 publications

Applications of Spatially Localized Active-Intensity Vectors for Sound-Field visualization

Applications of Spatially Localized Active-Intensity Vectors for Sound-Field visualization

A Novel Design and Implementation of Imaging Chip Using AXI Protocol for MPSOC on FPGA

Biometric Security and Internet of Things (IoT)

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