Geeganage Thilini Weerasuriya

Blockchain can be introduced to use cases in the built environment where reliability of transaction records is paramount. Blockchain facilitates decentralised, cryptographically secure, trustworthy, and immutable recordkeeping of transactions. However, more research is urgently required to understand the process and complications in implementing blockchain solutions in the built environment. This paper demonstrates a methodology for developing a blockchain system starting from problem analysis, selection of blockchain platform, system modelling, prototype development, and evaluation. The evolutionary prototyping model was selected as the software development methodology for the use case of property transactions. A systematic process protocol involving the multi-criteria decision-making method, Simple Multi Attribute Rating Technique (SMART), was used to select Hyperledger Fabric as the most suitable blockchain platform for the prototype. The system architecture facilitates a simplified, lean property transaction process implemented through chaincode (smart contract) algorithms and graphical user interfaces. System evaluation through test cases allowed iterative improvements, leading to an incubation-ready software prototype. The contribution to knowledge of this paper is in the demonstration of the process to follow to implement a blockchain solution for a specific domain. The findings provide the foundation for developing proofs of concept for other potential applications of blockchain in the built environment.

The construction industry has dynamic supply chains with multiple suppliers usually engaged in short-term relationships. Government legislation, novel types of payment agreements, conventional information technology solutions, and supply chain management best practices have endeavoured to solve payment-related financial issues in the construction industry, which are mainly caused by the complexities of the construction supply chain. Nevertheless, payment-related issues persist as one of the key challenges in the industry. Applications of blockchain technology–a trusted, distributed data storing mechanism–along with smart contracts are gaining focus as solutions for complex interorganisational processes. A smart contract is a self-executing script that codifies a set of rules or agreements between multiple parties and runs across the blockchain network. This paper identifies the suitability of blockchain and smart contract technologies in solving payment issues in the construction industry. An expert forum of construction industry stakeholders served as the primary data collection method through a structured questionnaire. The key finding of the paper is that blockchain and smart contract powered solutions can significantly mitigate the payment and related financial issues in the construction industry, including partial payments, nonpayments, cost of finance, long payment cycle, retention, and security of payments.

In Wireless Sensor Networks (WSNs) a large number of wirelessly-connected sensor motes work in collaboration to achieve a common goal such as detection of earthquakes, tracking animal movement, monitoring infrastructure or a volcano, and process control. Among the deployed WSNs, environmental sensing is important as a considerable number of the WSN applications have been developed on environmental sensing. The collected environment sensor data such as humidity, temperature, and air quality and soil moisture can be analyzed for better decision making. Moreover, actuator systems can be operated based on the sensor data. This paper presents a survey of already deployed WSNs for environmental sensing, comparing their scale of deployment, topologies and architectures, and routing protocols.

Speech recognition, natural language processing, language translation and deep learning researches are bridging the communication gap between humans as well as between humans and machines. Sinhala is a native language in Sri Lanka which is being used by 19 million people approximately. The growth of Sinhala natural language processing tools is less when compared to European and other Asian Languages. A lemmatizer for Sinhala can be used for the morphological analysis and is an essential module in Sinhala language processing mechanisms. Lemmatizing is a complex process in morphological analyzing where base/root of words are derived. There is not much work published focusing on lemmatizer approaches for Sinhala. This paper presents a rule based lemmatizing approach which can be used to determine the base form of Sinhala words with an accuracy of 77.3%. It differs from similar works because the data used in the research are extracted from social media.