Robust sound event detection in bioacoustic sensor networks

Bioacoustic sensors, sometimes known as autonomous recording units (ARUs), can record sounds of wildlife over long periods of time in scalable and minimally invasive ways. Deriving per-species abundance estimates from these sensors requires detection, classification, and quantification of animal vocalizations as individual acoustic events. Yet, variability in ambient noise, both over time and across sensors, hinders the reliability of current automated systems for sound event detection (SED), such as convolutional neural networks (CNN) in the time-frequency domain. In this article, we develop, benchmark, and combine several machine listening techniques to improve the generalizability of SED models across heterogeneous acoustic environments. As a case study, we consider the problem of detecting avian flight calls from a ten-hour recording of nocturnal bird migration, recorded by a network of six ARUs in the presence of heterogeneous background noise. Starting from a CNN yielding state-of-the-art accuracy on this task, we introduce two noise adaptation techniques, respectively integrating short-term (60 milliseconds) and long-term (30 minutes) context. First, we apply per-channel energy normalization (PCEN) in the time-frequency domain, which applies short-term automatic gain control to every subband in the mel-frequency spectrogram. Secondly, we replace the last dense layer in the network by a context-adaptive neural network (CA-NN) layer. Combining them yields state-of-the-art results that are unmatched by artificial data augmentation alone. We release a pre-trained version of our best performing system under the name of BirdVoxDetect, a ready-to-use detector of avian flight calls in field recordings.Comment: 32 pages, in English. Submitted to PLOS ONE journal in February 2019; revised August 2019; published October 201

Improving driver behaviour by design: a cognitive work analysis methodology

Within the European Community both the environmental and safety costs of road transport are unacceptably high. ‘Foot-LITE’ is a UK project which aims to encourage drivers to adopt ‘greener’ and safer driving practices, with real-time and retrospective feedback being given both in-vehicle and off-line. This paper describes the early concept development of Foot-LITE, for which a Cognitive Work Analysis (CWA) was conducted. In this paper, we present the results of the first phase of CWA – the Work Domain Analysis, as well as some concept interface designs based on the WDA to illustrate its application. In summary, the CWA establishes a common framework for the project, and will ultimately contribute to the design of the in-vehicle interfac

The Ambient Horn: Designing a novel audio-based learning experience

The Ambient Horn is a novel handheld device designed to support children learning about habitat distributions and interdependencies in an outdoor woodland environment. The horn was designed to emit non-speech audio sounds representing ecological processes. Both symbolic and arbitrary mappings were used to represent the processes. The sounds are triggered in response to the children’s location in certain parts of the woodland. A main objective was to provoke children into interpreting and reflecting upon the significance of the sounds in the context in which they occur. Our study of the horn being used showed the sounds to be provocative, generating much discussion about what they signified in relation to what the children saw in the woodland. In addition, the children appropriated the horn in creative ways, trying to ‘scoop’ up new sounds as they walked in different parts of the woodland

A Platform for the Analysis of Qualitative and Quantitative Data about the Built Environment and its Users

There are many scenarios in which it is necessary to collect data from multiple sources in order to evaluate a system, including the collection of both quantitative data - from sensors and smart devices - and qualitative data - such as observations and interview results. However, there are currently very few systems that enable both of these data types to be combined in such a way that they can be analysed side-by-side. This paper describes an end-to-end system for the collection, analysis, storage and visualisation of qualitative and quantitative data, developed using the e-Science Central cloud analytics platform. We describe the experience of developing the system, based on a case study that involved collecting data about the built environment and its users. In this case study, data is collected from older adults living in residential care. Sensors were placed throughout the care home and smart devices were issued to the residents. This sensor data is uploaded to the analytics platform and the processed results are stored in a data warehouse, where it is integrated with qualitative data collected by healthcare and architecture researchers. Visualisations are also presented which were intended to allow the data to be explored and for potential correlations between the quantitative and qualitative data to be investigated

Intimate interfaces in action: assessing the usability and subtlety of emg-based motionless gestures

Mobile communication devices, such as mobile phones and networked personal digital assistants (PDAs), allow users to be constantly connected and communicate anywhere and at any time, often resulting in personal and private communication taking place in public spaces. This private -- public contrast can be problematic. As a remedy, we promote intimate interfaces: interfaces that allow subtle and minimal mobile interaction, without disruption of the surrounding environment. In particular, motionless gestures sensed through the electromyographic (EMG) signal have been proposed as a solution to allow subtle input in a mobile context. In this paper we present an expansion of the work on EMG-based motionless gestures including (1) a novel study of their usability in a mobile context for controlling a realistic, multimodal interface and (2) a formal assessment of how noticeable they are to informed observers. Experimental results confirm that subtle gestures can be profitably used within a multimodal interface and that it is difficult for observers to guess when someone is performing a gesture, confirming the hypothesis of subtlety

Improving driver behaviour by design : a cognitive work analysis methodology

Within the European Community both the environmental and safety costs of road transport are unacceptably high. ‘Foot-LITE’ is a UK project which aims to encourage drivers to adopt ‘greener’ and safer driving practices, with real-time and retrospective feedback being given both in-vehicle and off-line. This paper describes the early concept development of Foot-LITE, for which a Cognitive Work Analysis (CWA) was conducted. In this paper, we present the results of the first phase of CWA – the Work Domain Analysis, as well as some concept interface designs based on the WDA to illustrate its application. In summary, the CWA establishes a common framework for the project, and will ultimately contribute to the design of the in-vehicle interface

MarinEye - A tool for marine monitoring

This work presents an autonomous system for marine integrated physical-chemical and biological monitoring – the MarinEye system. It comprises a set of sensors providing diverse and relevant information for oceanic environment characterization and marine biology studies. It is constituted by a physicalchemical water properties sensor suite, a water filtration and sampling system for DNA collection, a plankton imaging system and biomass assessment acoustic system. The MarinEye system has onboard computational and logging capabilities allowing it either for autonomous operation or for integration in other marine observing systems (such as Observatories or robotic vehicles. It was designed in order to collect integrated multi-trophic monitoring data. The validation in operational environment on 3 marine observatories: RAIA, BerlengasWatch and Cascais on the coast of Portugal is also discussed.info:eu-repo/semantics/publishedVersio

A File System Abstraction for Sense and Respond Systems

The heterogeneity and resource constraints of sense-and-respond systems pose significant challenges to system and application development. In this paper, we present a flexible, intuitive file system abstraction for organizing and managing sense-and-respond systems based on the Plan 9 design principles. A key feature of this abstraction is the ability to support multiple views of the system via filesystem namespaces. Constructed logical views present an application-specific representation of the network, thus enabling high-level programming of the network. Concurrently, structural views of the network enable resource-efficient planning and execution of tasks. We present and motivate the design using several examples, outline research challenges and our research plan to address them, and describe the current state of implementation.Comment: 6 pages, 3 figures Workshop on End-to-End, Sense-and-Respond Systems, Applications, and Services In conjunction with MobiSys '0