Research Publications Authored by SLIIT Staff

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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.

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2005 - 200912010 - 20191

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    Efficient Agricultural Sensor Network with Disease Detection
    (IEEE, 2019-12-05) Gunathilaka, M. D. N; Lokuliyana, S; Udurawana, A. W. G. C; Dissanayaka, D. M. A. S; Jayakody, A
    The smart Agriculture concept is a new trending topic in making traditional agriculture task automation to make them more effective and efficient to suit current human requirements. With machine learning and image processing technologies those tasks are made more robust and accurate while maintaining the low cost made this research inspired to adopt Sri Lankan farmers to develop a real-time disease detection monitoring system with wireless sensor node for crops, so that would be able to harvest and store energy for battery-free operation using supercapacitors and technologies such as Maximum Power Point Tracking. The main outcomes of this nodes are to monitor the growth environment and also the crop for diseases by using image processing and machine learning techniques in order to cultivate a better fruit overall. The wireless sensor node can be adapted to be used on multiple types of remote farms. Pineapple (Ananas comosus) was selected as the test crop for the research which is a fruit grown widely in tropical countries in large fields. The texture, shape of the fruit and the taste of pineapple changes due to various conditions. The final system makes monitoring the crop for diseases a lot effective while making monitoring the growth conditions more efficient compared with what's available on the market.
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    PublicationOpen Access
    An algorithm for energy driven cluster head rotation in a distributed wireless sensor network
    (Colombo, 2005-12-15) Gamwarige, S; Kulasekere, E. C
    Wireless sensor networks (WSNs) consists of large number of inexpensive, low-power, sensors that can be placed in an ad hoc fashion to form a communication network. Efficient techniques for inter sensor communication and information gathering is critical for prolonging the lifetime of the sensor network. Clustering provides an effective way for extending the lifetime of a sensor network. In this paper we propose a distributed and energy driven clustering algorithm where the cluster heads are selected based on relative residual energy level of sensors. Furthermore the cluster head candidacy selection phase, and the cluster head candidacy rotation among phases is triggered only when any of cluster heads energy drops below a dynamic threshold computed by the algorithm. As a result, the overheads in the inter sensor communications will be reduced and thereby the proposed algorithm will favor more powerful nodes over the weaker ones to prolong the lifetime of the entire sensor network in both homogeneous and heterogeneous sensor networks. The results have shown that the the proposed algorithm performs better when compared to existing algorithms such as LEACH, SEP, HEED and ANTCLUST based on the Percentage Node Alive (PNA) and the First Node Dies (FND) metrics.