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Author: search.filters.author.Perera, JSubject: search.filters.subject.Blockchain

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    Optimizing Gas Efficiency in Ethereum Smart Contracts using Design Pattern Refinement and Complexity Reduction
    (Institute of Electrical and Electronics Engineers Inc., 2025-12-09) Weedagamaarachchi K.S; Vithanage H.D; Dehipola H.M.S.N; Manditha K.D.R; Jayasinghearachchi, V; Perera, J
    Smart contracts on the Ethereum blockchain enable automation and transparency in decentralized applications; however, their scalability is often constrained by high gas costs resulting from inefficient code design. This research investigates the relationship between cyclomatic code complexity and gas consumption, proposing a design pattern-based approach to optimize gas efficiency in Ethereum smart contracts. Three common Solidity patterns Factory, Registry, and State Machine were optimized using both existing and novel techniques, including variable packing, the use of fixed-size data types (uint256, bytes32), immutable variables, and mapping simplification. These optimizations were implemented and tested within a real-world coco peat supply chain management system to measure their impact on gas usage. Experimental results showed that deployment gas costs decreased by approximately 19% and runtime execution gas by around 14%, confirming that design-level optimization can significantly reduce costs without affecting functionality. The findings demonstrate that structured refinement of contract design can enhance scalability, making blockchain-based enterprise solutions more efficient and economically sustainable.
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    Smart Agricultural Platform for Sri Lankan Farmers with Price Prediction, Blockchain Security, and Adaptive Interfaces
    (Institute of Electrical and Electronics Engineers Inc., 2025-06-25) Kuruppu K.A.G.S.R; Kandambige S.T; Perera W.H.T.H.; Cooray N.T.L; Nawinna, D; Perera, J
    Improper management of seed demand in Sri Lanka's agricultural sector can result in market imbalances, affecting farmers' decision-making and supply chain efficiency. This research introduces an integrated system for monitoring vegetable seed demand using digital technologies. The proposed system utilizes machine learning techniques to predict vegetable prices, a blockchain network for secure transactions, and a reward-based system to encourage user engagement. It also incorporates an adaptive user interface to accommodate different levels of digital literacy, ensuring accessibility for all farmers, especially senior citizens. Furthermore, the system features an AI Chatbot powered by Langchain and Pinecone, offering domain-specific responses and real-time support for farmers. The solution aims to combine advanced technology with agricultural practices to improve seed demand forecasting, promote transparency in transactions, and ensure a more efficient supply chain. This paper presents a multi-component agricultural platform that integrates predictive analytics, blockchain-secured transactions, gamified incentives, and adaptive user interfaces to support farming decision-making. The system combines machine learning for price forecasting, dynamic reward mechanisms to drive user engagement, and personalized UI/UX optimizations tailored for diverse user groups, including senior farmers. A multilingual AI-powered chatbot enhances accessibility and real-time support, enabling a robust, transparent, and inclusive digital solution for agricultural supply chain management.
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    Smart Agricultural Platform for Sri Lankan Farmers with Price Prediction, Blockchain Security, and Adaptive Interfaces
    (Institute of Electrical and Electronics Engineers Inc., 2025) Kuruppu K.A.G.S.R.; Kandambige S.T; Perera W.H.T.H; Cooray N.T.L; Nawinna, D; Perera, J
    Improper management of seed demand in Sri Lanka's agricultural sector can result in market imbalances, affecting farmers' decision-making and supply chain efficiency. This research introduces an integrated system for monitoring vegetable seed demand using digital technologies. The proposed system utilizes machine learning techniques to predict vegetable prices, a blockchain network for secure transactions, and a reward-based system to encourage user engagement. It also incorporates an adaptive user interface to accommodate different levels of digital literacy, ensuring accessibility for all farmers, especially senior citizens. Furthermore, the system features an AI Chatbot powered by Langchain and Pinecone, offering domain-specific responses and real-time support for farmers. The solution aims to combine advanced technology with agricultural practices to improve seed demand forecasting, promote transparency in transactions, and ensure a more efficient supply chain. This paper presents a multi-component agricultural platform that integrates predictive analytics, blockchain-secured transactions, gamified incentives, and adaptive user interfaces to support farming decision-making. The system combines machine learning for price forecasting, dynamic reward mechanisms to drive user engagement, and personalized UI/UX optimizations tailored for diverse user groups, including senior farmers. A multilingual AI-powered chatbot enhances accessibility and real-time support, enabling a robust, transparent, and inclusive digital solution for agricultural supply chain management.