Best Paper Award at IJCAI 201315th July 2013
Our paper titled "A hidden Markov model-based acoustic cicada detector for crowdsourced smartphone biodiversity monitoring" received the award for Outstanding Student Paper at the International Joint Conference for Artificial Intelligence (IJCAI), 2013. The conference was held in Beijing, China, and the paper was presented by Davide Zilli.
Davide Zilli receiving the award
Abstract: Automated acoustic recognition of species aims to provide a cost-effective method for biodiversity monitoring. This is particularly appealing for detecting endangered animals with a distinctive call, such as the New Forest cicada. To this end, we pursue a crowdsourcing approach, whereby the millions of visitors to the New Forest will help to monitor the presence of this cicada by means of a smartphone app that can detect its mating call. However, current systems for acoustic insect classification are aimed at batch processing and not suited to a real-time approach as required by this system, because they are too computationally expensive and not robust to environmental noise. To address this short-coming we propose a novel insect detection algorithm based on a hidden Markov model to which we feed as a single feature vector the ratio of two key frequencies extracted through the Goertzel algorithm. Our results show that this novel approach, compared to the state of the art for batch insect classification, is much more robust to noise while also reducing the computational cost.
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Energy Harvesting Book Chapter30th June 2010
My book chapter on "Wireless Devices and Sensor Networks," that I co-authored with Dr Alex Weddell and Dr Nick Harris has just been published! The book, titled "Energy Harvesting for Autonomous Systems", is published by Artech House, and edited by Professor Neil White and Dr Steve Beeby. The majority of my chapter is (at least currently) available to read on Google Books.
The chapters of the book are:
Wireless Devices and Sensor Networks
Photovoltaic Energy Harvesting
Energy Harvesting Network's Data Repository Launched13th February 2012
The Energy Harvesting Network, coordinated by myself and Prof Steve Beeby at the University of Southampton, have launched the Network's 'Data Repository' - an online catalogue for researchers worldwide to share data on ambient energy availability - for example acceleration levels, solar irradience, or wind speeds. It is hoped that, by using a common dataset, this will encourage the comparitive evaluation of energy harvesters and fuel advances in the field.
Natuarlly, the repository will only ... [more]