Mosquito-borne disease has a major impact on human health, income and mortality in over 100 countries affecting over half the world’s population. Malaria alone is transmitted by over 40 species of mosquito, caused 627,000 deaths worldwide in 2012 and reduced African GDP by over $12bn. Control programmes rely heavily on mapping and modelling tools which are limited in that they are static in time and space. We will embed acoustic monitoring sensors in handheld devices such as smartphones and wristbands, which can detect (unique, species-specific) wing-beats from mosquitoes and alert the carrier to their presence. Detection data will be available for real-time analysis by researchers, who will combine it with ultra-high resolution (30m pixel) remote imaging to determine environmental factors such as vegetation composition and structure and distance to water bodies. This multi-layered data will support the design of better-targeted, more effective vector control programmes.

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The New Forest Cicada (Cicadetta montana s. str.) is the only cicada native to the UK. During May to July it sings with a very characteristic high-pitched song, which is at the limits of human hearing, and is particularly difficult for most adults to hear. Sightings of the cicada within the New Forest date back to 1812, but the last unconfirmed sighting was in 2000. However, it's quite likely that colonies remain undiscovered in less visited parts of the forest. The New Forest Cicada Project aims to equip the millions of visitors to the forest with a smart phone app that can detect and recognise the song of the cicada, and hopes to rediscover it in 2013.

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Cape Town's public transit authorities are in need for data to understand how to improve quality of service and increase the accountability of transport operators. CiTiVAN proposes a phone based rating, payment and positioning system that promotes transparency and accountability from the bottom up, giving people a voice about the service they receive.

For more information click here. Note that I have now left the project, which is still on-going. For up-to-date info please visit senseable.mit.edu.

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From the project's press release, January 2014: Over the past weeks, MIT researchers and LAAB Studio have deployed a system of human-borne sensors to assess and compare air pollution in Hong Kong and Shenzhen. Results are presented as a dynamic map called 'One Country, Two Lungs', currently on show at the Hong Kong / Shenzhen Bi-City Biennale of Urbanism and Architecture (until the end of February 2014). The installation highlights an asymmetric exposure to pollution between the inhabitants of Hong Kong and Shenzhen, showing how air quality across one of the world’s largest metropolitan areas changes step by step. One Country Two Lungs also provides a glimpse into how new applications of sensor and tracking technology can be used for monitoring air pollution in cities on a personal, human scale.

Read more on the One Country, Two Lungs website.

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Intelligent energy management is a key challenge in Wireless Sensor Networks. The choice of an appropriate routing algorithm constitutes a critical factor, especially in unstructured networks where, due to their dynamic nature, a reactive routing protocol is necessary. Such networks often favour packet flooding to fulfil this need. One such algorithm is IDEALS, a technique proposed in the literature, which balances energy consumed with information delivered. This paper evaluates the use of a single-path solution with IDEALS to increase efficiency. Simulation results comparing the two approaches show that the single-path algorithm outperforms flooding in terms of energy consumption for any network size. Furthermore the benefit of IDEALS is preserved as its combination with the single-path algorithm maximises information throughput.

Wireless Sensor Networks often harvest energy from the environment in order to reduce battery replacement and potentially achieve perpetual operation. However, the energy sources used, such as solar and wind power, are variable and their availability can highly influence the lifetime of the nodes. In particular, by knowing in advance what the available resources are, it becomes possible to tune sensing patterns and communication algorithms, coordinating the consumption with the intake. This project models a network of nodes in order to discover how and in what way the above issues can be addressed. To do this, weather forecast information from the web are combined with local observations, collected through a custom-made deployment of TI MSP430 nodes with a miniature wind turbine.