As vectors of malaria, dengue, zika, and yellow fever, mosquitoes are considered one of the more severe worldwide health hazards. Widespread surveillance of mosquitoes is essential for understanding their complex ecology and behaviour, and also for predicting and formulating effective control strategies against mosquito-borne diseases. One technique involves using bioacoustics to automatically identify different species from their wing-beat sounds during flight. In this dataset, we collect sounds of three species of mosquitoes: Aedes Aegypti, Culex Quinquefasciatus & Pipiens, and Culiseta. These species were collected and reproduced in the laboratory of the Natural History Museum of Funchal, in Portugal, by entomologists trained to recognize and classify mosquitoes. For collecting the samples, we used a microcontroller and a mobile phone. The dataset presents audio samples collected with different sampling rates, where 34 audio features characterize each sound file, making it is possible to observe how mosquito populations vary heterogeneously. This dataset provides the basis for feature extraction and classification of flapping-wing flight sounds that could be used to identify different species.
IoT has been widely adopted by HCI communities and citizen scientists to sense and control the surrounding environments. While their applications are mostly reported in urban settings, they remain scarce in aquatic settings. Oceans are undergoing an immense increase of human generated pollution ranging from noise to marine litter, where current USV solutions to detect its impact on environment remain at high cost. In our study, we design a first low-cost, long-range, radio controlled USV, based on IoT and LoRa, intended to be used for aquatic expeditions collecting environmental telemetry. We gather temperature, humidity, GPS position, footage and provide a mobile interface for remote controlling the USV. With this pilot study, we provide an initial study of the suitable simplistic GUI for long-range remote sensing in aquatic setting. We discuss the findings and propose future applications and Internet of Water Things as future research direction.
The Internet of Things (IoT) is opening new possibilities for sensing, monitoring and actuating in urban environments. They support a shift to a hybrid network of humans and things collaborating in production, transmission and processing of data through low-cost and low power devices connected via longrange (LoRa) wide area networks (WAN). This paper describes a 2-player duel game based on IoT controllers and LoRa radio communication protocol. Here we report on the main evaluation dimensions of this new design space for games, namely: i) game usability (SUS) leading to an above average score; ii) affective states of the players (SAM) depicting pleasant and engaging gameplay, while players retain control; iii) radio coverage perception (RCP) showing that most participants did not change their perception of the radio distance after playing. Finally, we discuss the findings and propose future interactive applications to take advantage of this design space.
The monitoring of environmental parameters is indispensable for controlling mosquito populations. The abundance of mosquitoes mainly depends on climate conditions, weather and water (i.e., physicochemical parameters). Traditional techniques for immature mosquito surveillance are based on remote sensing and weather stations as primary data sources for environmental variables, as well as water samples which are collected in the field by environmental health agents to characterize water quality impacts. Such tools may lead to misidentifications, especially when comprehensive surveillance is required. Innovative methods for timely and continuous monitoring are crucial for improving the mosquito surveillance system, thus, increasing the efficiency of mosquitoes' abundance models and providing real-time prediction of high-risk areas for mosquito infestation and breeding. Here, we illustrate the design, implementation, and deployment of a novel IoT-based environment monitoring system using a combination of weather and water sensors with a real-time connection to the cloud for data transmission in Madeira Island, Portugal. The study provides an approach to monitoring some environmental parameters, such as weather and water, that are related to mosquito infestation at a fine spatiotemporal scale. Our study demonstrates how a combination of sensor networks and clouds can be used to create a smart and fully autonomous system to support mosquito surveillance and enhance the decision-making of local environmental agents.
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