Chathura Suduwella

Identifying Mosquito Breeding Sites via Drone Images

Public Health Inspectors (PHIs) in Sri Lanka are facing a problem of identifying certain mosquito breeding sites since they cannot easily reach places such as roof gutters, overhead water tanks, inaccessible rooftops and cement materials which are capable of retaining water. The goal of a such inspection of suspected sites is to reduce the number of dengue patients by eradicating dengue mosquito habitats. Due to the retention of water in the aforementioned sites for a long period of time, those places tend to be full of lichens. In general, lichens are visible in dark color. This characteristic helps to identify prolonged water retention areas. With the rapid advancement of technology, the drone has been created as one of the most cost effective apparatus to capture the places that a human cannot access. With respect to the aforesaid context, this paper presents a simple and a novel approach to identify mosquito breeding sites via drone images. The proposed approach processes images captured from a drone to identify possible sites where stagnant water may retain and highlights if such areas are apparent within the image. The evaluation process found that the proposed method, produces a satisfactory level of accuracy in identification of possible water retention areas and the final results depend on the drone camera tilt angle and the effect of shadows.

Wireless Sensing: What Simplicity Has to Offer?

We argue that, a wireless sensor does not have to implement a full networking stack in order to be a part of an energy efficient sensing application as long as it can deliver its sensed data to an Internet connected device over a single hop. Current hardware industry trends indicate the possibility of implementing wireless sensors for a low cost with simple capabilities. This poster highlights our preliminary work aligned with this trend and aims to open a discussion on this topic.

Listening to the Giants: Using Elephant Infra-Sound to Solve the Human-Elephant Conflict

The continuing human-elephant conflict in Sri Lanka has resulted in loss of human as well as elephant lives. Detecting and localizing elephants is an essential component of any viable solution to this problem. Currently, we conduct feasibility tests on using low cost sensors to detect elephants from a long distance, leveraging the infra-sounds emitted by them. In this paper we present the test environment that we have set up for this purpose and some preliminary, but promising results.

An Empirical Study of WiFi-based Radio Tomographic Imaging

Radio Tomographic Imaging (RTI) enables device free localization of physical objects by using signal attenuation in wireless networks. In this paper, we explore how existing RTI methods can be used in WiFi networks to do tomographic imaging. Moreover we analyze and evaluate the properties that affect the accuracy of WiFi tomographic imaging process.

A Machine Learning Approach for Identifying Mosquito Breeding Sites via Drone Images

Dengue is one of the deadly and fast spreading diseases in Sri Lanka. The female Aedes mosquito is the dengue vector and these mosquitoes breed in clear and non-flowing water. The Public Health Inspectors (PHIs) are tasked with detecting and eliminating such water collection areas. However, they face the problem of detecting potential breeding sites in hard-to-reach areas. With the technological development, the drones come as one of the most cost effective unmanned vehicles to access the places that a man cannot access. This paper presents a novel approach for identifying mosquito breeding areas via drone images through the distinct coloration of those areas by applying the Histogram of Oriented Gradients (HOG) algorithm. Using the HOG algorithm, we detect potential water retention areas using drone images.