Despite the fact that the ocean plays a role in everything from the air we breathe to daily weather and climate patterns, we know very little about our ocean. Underwater wireless sensor network (UWSN) is one of the options helping us to discover some domains such as natural assets and underwater resource exploration. However, the acoustic signal is the only suitable option in underwater communication in the absence of radio waves, which face a number of challenges under this environment. To overcome these issues, many routing schemes are introduced by researchers though energy consumption is still a challenge in underwater communication. To overcome the issue of rapid energy consumption, a reliable and energy-efficient routing method is introduced that avoids the redundant forwarding of data; hence, it achieves energy efficiency and eventually prolongs the network lifetime. Simulation results support the claim that the proposed scheme achieves energy efficiency along higher delivery ratio by reducing the data transmission error rate during the routing decisions.
Dengue fever is among the most dangerous infectious viral diseases transmitted through the bite of infected Aedes Aegypti mosquitoes. One way to decline the spread of dengue is by raising awareness to the community about mosquito habitats through continuous surveillance. The traditional surveillance techniques of Aedes Aegypti are difficult, time taking, and can lead to severe health risks. This paper presents a possible way of dengue vector surveillance through acoustic signals generated by wingbeat of Aedes Aegypti using the sequential model of convolutional neural network. Mel-frequency spectrum is given as an input feature to the sequential model that significantly improves classification performance up to 93% accuracy. The system generates notification through a specially designed mobile application to alert detected dengue vectors in the region. It is helpful in continuous monitoring of dengue vectors to take early precautionary measures for effective control and prevention.
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