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Author: search.filters.author.Wijekoon, JEnd date: 2021

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Now showing 1 - 10 of 53
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    A Geophone Based Surveillance System Using Neural Networks and IoT
    (IEEE, 2020-12-10) Hettigoda, S; Jayaminda, C; Amarathunga, U; Thaha, S; Wijesundara, M; Wijekoon, J
    Securing our assets and properties from intruders and thieves has become increasingly challenging as intruders become technology aware. The most common approach to monitor physical assets is CCTV. However, this approach has a number of technical limitations in addition to the cost. The CCTV camera location is visible to the intruder and intruder can also identify possible blind spots in the CCTV coverage area. In this paper, we introduce a novel method to secure physical assets using Geophones, Neural Networks, and IoT Platforms. This can either be used stand alone or to complement existing CCTV systems. In this approach, the system monitors vibrations on ground to detect intruders. We have achieved up to 93.90% overall accuracy for person identification. The system is invisible to intruders and covers a large area with a smaller number of nodes, thereby reducing the cost of ownership.
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    CoviDefender: Digital Personal Guard For Defending Against COVID19
    (IEEE, 2021-09-30) Dayarathna, p; Kumara, I; Ranaweera, D; Nawinna, D. P; Karunaratne, G; Wijekoon, J
    In late 31 December 2019, a cluster of unexplained pneumonia cases was reported in Wuhan, China [1]. A few days later, the causative agent of this mysterious pneumonia was identified as the new COVID-19 virus. Currently, it has been spreading for more than one and a half years and has lost a huge number of lives all over the world. Most people faced this disaster because of their ignorance, carelessness and lack of updates. By the way most people are in lack of knowledge regarding COVID-19 pandemic, symptoms and what should do to survive from that. Those issues are great problems nowadays. “CoviDefender” is set to offer a solution to this worldwide COVID-19 pandemic problem. This is a new technological solution from a mobile application. “CoviDefender” is a Smart Assistant for Defending against COVID-19 Pandemic. This can be described as a solution to the ignorance and carelessness of the people who have been the main cause of the spread of this epidemic.
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    Power Profiling: Assessment of Household Energy Footprints
    (IEEE, 2021-03-06) Wijesinghe, V; Perera, M; Peiris, C; Vidyaratne, P; Nawinna, D. P; Wijekoon, J
    Reduced energy footprint is considered an indicator of efficiency around the world. Having insights into electricity consumption behavior of individuals or families across the day is very useful in efficient management of electricity. In this paper, we present s study that focused on identifying patterns in the monthly electricity consumption profiles of a single household with the K-means clustering algorithm. The data required for this study was collected through a survey in the Sri Lankan context. The survey mainly captured the factors affecting electricity consumption. After proving the demand of electricity is dependable on the data that has been collected, they will be keyed into data models/ profiles that will be built using clustering algorithms. A load profile will be designed using K-means to identify usage patterns of a household on a monthly basis. The parameters that affect the electricity consumption were tested and trained using the SVM algorithm. The outcomes of this study include; identifying the factors contributing to the electricity consumption, identifying electricity consumption patterns, identifying the energy footprint of individuals or families and predicting the future electricity requirements. The results of this study provide many advantages for both consumers and suppliers in efficient management of electricity. It also provides significant impacts in both micro and macro levels through enabling efficient decision-making regarding management of electricity.
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    Smart Agriculture Prediction System for Vegetables Grown in Sri Lanka
    (IEEE, 2021-10-27) Gamage, R; Rajapaksa, H; Sangeeth, A; Hemachandra, G; Wijekoon, J; Nawinna, D. P
    Agriculture planning plays a dominant role in the economic growth and food security of agriculture-based countries such as Sri Lanka. Even though agriculture plays a vital role, there are still several major complications to be addressed. Some of the major complications are lack of knowledge about yield and price resulting in the farmers selecting crops based on experience. Machine learning has a great potential to solve these complications. To this end, this paper proposes a novel system comprises of a mobile application, SMS (Short Message Service), and API (Application Programming Interface) with yield prediction, price prediction, and crop optimization. Several machine learning algorithms were used for yield and price predictions while a generic algorithm was used to optimize crops. The yield was predicted considering the environmental factors while the price was predicted considering supply and demand, import and export, and seasonal effect. To select the best suitable crops to cultivate, the output of yield and price prediction have been used. Yield prediction has been implemented using elastic net, ridge, and multilinear regression. R2 of yield prediction is varied from 0.74 to 0.89 while RMSE value is between 15.69 and 35.05. Price prediction has been implemented using the algorithms of Gradient Boosting Tree, Random Forest, Facebook Prophet, and R2 is varied from 0.72 to 0.92 while RMSE value is between 26.81 and 140.72. Crop optimization has been implemented using the genetic algorithm.
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    CoviDefender: Digital Personal Guard For Defending Against COVID19
    (IEEE, 2021-09-30) Dayarathna, P; Kumara, I; Ranaweera, D; Nawinna, D; Karunaratne, G; Wijekoon, J
    In late 31 December 2019, a cluster of unexplained pneumonia cases was reported in Wuhan, China [1]. A few days later, the causative agent of this mysterious pneumonia was identified as the new COVID-19 virus. Currently, it has been spreading for more than one and a half years and has lost a huge number of lives all over the world. Most people faced this disaster because of their ignorance, carelessness and lack of updates. By the way most people are in lack of knowledge regarding COVID-19 pandemic, symptoms and what should do to survive from that. Those issues are great problems nowadays. “CoviDefender” is set to offer a solution to this worldwide COVID-19 pandemic problem. This is a new technological solution from a mobile application. “CoviDefender” is a Smart Assistant for Defending against COVID-19 Pandemic. This can be described as a solution to the ignorance and carelessness of the people who have been the main cause of the spread of this epidemic.
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    Effective use of network device state information for network path selection
    (IEEE, 2017-01-27) Wijekoon, J; Abeygunawardhana, P. K. W
    Network path selection defines the methodology of selecting the best routes and forwarding traffic in a network service provider (NSP). NSPs use routing protocols that are optimized for a single arbitrary metric (i.e., administrative weight), which is commonly calculated according to the link state information, to select network paths. Despite the advantages, link-state protocols lack the ability to select network paths by considering the states of network devices such as the effect of routers for network path selection. Apparently, studying possible techniques for selecting network paths based on the state information of network devices, e.g., routers, has become obligatory. This paper hypothesis to calculate a composite path selection metric by employing the state information of network devices; the proposed method selects the network paths based on the cumulative packet traveling time. By simulating proposed method using an ISP topology, the proposed method is examined for the effectiveness of using network device state information for network path selection.
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    On the effectiveness of using network device state information for network path selection
    (Elsevier, 2018-01-01) Wijekoon, J; Amunugama, D; Nishi, H
    Network path selection defines the methodology of selecting the best routes and forwarding traffic in a network service provider (NSP). NSPs use routing protocols that are optimized for a single arbitrary metric (i.e., administrative weight), which is commonly calculated according to the link state information, to select network paths. Despite the advantages, link-state protocols lack the ability to select network paths by considering the states of network devices such as the effect of routers for network path selection. Apparently, studying possible techniques for selecting network paths based on the state information of network devices, e.g., routers, has become obligatory. This paper studies the effectiveness of using network device state information for network path selection by presenting the Extended Server Link Router state Routing Protocol (ESLR). ESLR uses the state information of network devices as parameters to calculate a composite route metric; ESLR selects the network paths based on the cumulative propagation delay. By simulating ESLR using an ISP topology, the proposed protocol is examined for the effectiveness of using network device state information for network path selection.
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    Trainko: poster abstract: train arrival time prediction system for Sri Lanka
    (acm.org, 2011-04-11) Jayawardena, A. N; Sachith, K; Wijekoon, J
    Transportation system is a massive enterprise with substantial direct and indirect effects on economic growth of a country, and train system is playing a major role of the transportation system. However, the train system in Sri Lanka is usually late and the passengers come to the stations without knowing the train arrival time, whereas the passengers waste their valuable time at the train station waiting for the trains. To this end, this paper proposes to the smarten Sri Lankan the train system by predicting the time a train reaches to its upcoming stations and sending the notifications to the subscribers about the arrival time to their stations. Subscribers then can reach their station whenever the train is reaching to the station or they can use any other means of transportation if the train is late.
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    A Method to Generalize DNS TTL Value Calculation
    (IEEE, 2018-08-08) Peiris, N; Amunugama, D; Wijekoon, J
    The domain name service (DNS) is the service that resolves IP address(es) for a given fully qualified domain name (FQDN). The DNS is implemented as a hierarchical distributed cache system that stores the IP addresses of the FQDNs for a certain amount of time which is specified in time to live (TTL) value. The TTL value is a arbitrary value set by the authoritative name servers, aka service providers, and hence, the calculation of the TTL value is not defined in any literature the authors referred incurring that calculation of the TTL value is a mysterious part about the DNS service. To this end, this paper proposes a generalized method to calculate the TTL value of the DNS record using the performance of web server (i.e., authoritative name server) where an actual web request has to wait to until it is get served. This paper explains the proposed mathematical method of calculating the TTL values of DNS records and provides a detailed explanation of the used parameters with the reasons of selecting those parameters to calculate the TTL value.
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    Smart Plant Disorder Identification using Computer Vision Technology
    (IEEE, 2020-11-04) Manoharan, S; Sariffodeen, B; Ramasinghe, K. T; Rajaratne, L. H; Kasthurirathna, D; Wijekoon, J
    The soil composition around the world is depleting at a rapid rate due to overexploitation by the unsustainable use of fertilizers. Streamlining the availability of nutrient deficiency and fertilizer related knowledge among impoverished farming communities would promoter environmentally and scientifically sustainable farming practices. Thus, contributing to several Sustainable Development Goals set out by the United Nations. The most direct solution to the inappropriate fertilizer usage is to add only the necessary amounts of fertilizer required by plants to produce a significant yield without nutrition deficiencies. To this end this paper proposes a Smart Nutrient Disorder Identification system employing computer vision and machine learning techniques for identification purposes and a decentralized blockchain platform to streamline a bias-less procurement system. The proposed system yielded 88% accuracy in disorder identification, while also enabling secure, transparent flow of verified information.