Faculty Publications

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Publications by NITK Faculty

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Subject: search.filters.subject.Automation

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    Detecting phishing websites using automation of human behavior
    (Association for Computing Machinery, Inc acmhelp@acm.org, 2017) Rao, R.S.; Pais, A.R.
    In this paper, we propose a technique to detect phishing attacks based on behavior of human when exposed to fake website. Some online users submit fake credentials to the login page before submitting their actual credentials. He/She observes the login status of the resulting page to check whether the website is fake or legitimate. We automate the same behavior with our application (FeedPhish) which feeds fake values into login page. If the web page logs in successfully, it is classified as phishing otherwise it undergoes further heuristic filtering. If the suspicious site passes through all heuristic filters then the website is classified as a legitimate site. As per the experimentation results, our application has achieved a true positive rate of 97.61%, true negative rate of 94.37% and overall accuracy of 96.38%. Our application neither demands third party services nor prior knowledge like web history, whitelist or blacklist of URLS. It is able to detect not only zero-day phishing attacks but also detects phishing sites which are hosted on compromised domains. © 2017 Copyright held by the owner/author(s).
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    IoT based Smart Management of Poultry Farm and Electricity Generation
    (Institute of Electrical and Electronics Engineers Inc., 2018) Sitaram, K.A.; Ankush, K.R.; Anant, K.N.; Raghunath, B.R.
    Poultry is one of the most important growing economic segments of agricultural sector in India today. Nowadays because of standardized farming management and good manufacturing practices, chicken production in the world has been increasing gradually. In contemporary world automation plays a vital role and concept of Internet of Things (IOT) is also emerging very fast, there is an approach to convert traditional systems into automated systems. The paper focuses on automation of poultry farm using IoT technology to perform various management related things. The environmental factors which affect the health of chicken such as temperature, humidity, light and Ammonia gas are monitored and the manual jobs like food feeding, water supply system, cleanliness are managed. If all these parameters are maintained, the production and quality of chicken increases. Along with this, electricity is generated from the methane gas which is produced from the chicken manure and stored in battery. The management and monitoring of the farm can also be done through a web based system. Which keeps track of the management of poultry farm from anywhere and at any time. © 2018 IEEE.
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    Automation of Curing Using Prefabricated Sensors
    (Springer Science and Business Media Deutschland GmbH, 2021) Agarwalla, A.; Das, B.B.
    Curing is one of the universal phenomena followed after casting and finishing of concrete over an extended period of time, which helps to develop the compressive strength and durability by maintaining an optimum moisture and temperature condition. It keeps the concrete hydrated, restricts volumetric shrinkage, provides resistance to abrasion, freezing and thawing. There are many ways to cure concrete but, in this article, discussion will be on automation of curing using IoT and moisture sensors and relays which will likely replicate the lab condition on site by maintaining constant moisture content in concrete by supplying required amount of water. Generally, on site the curing process is carried out for 6–7 days once or twice a day at a large interval as a result of which the free moisture content falls and the rate of hydration decreases. It results in poor compressive strength and durability compared with laboratory samples because the 7 days compressive strength is not achieved which is more important than that of 28 days compressive strength which is successfully achieved in the lab. Various technologies used in this article will help in real-time monitoring of concrete condition with ease which will further be beneficial for the construction industry. This paper will cover how these technologies are integrated to automate the whole process, and its effect on compressive strength of concrete for which a consistent mix of M20, M25, M30 was prepared to compare the result of strength of concrete at 3, 7 and 28 days of curing in three different conditions, giving the strength of in-situ automatically cured concrete sample similar to that of laboratory cured concrete sample and an increase in 16.09% of compressive strength was observed with respect to concrete cured manually in site conditions. © 2021, Springer Nature Singapore Pte Ltd.
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    Safety Stock in Inventory Management and Wastage Analysis at Construction Sites
    (Springer Science and Business Media Deutschland GmbH, 2021) Paul, B.; Tondihal, S.; Das, B.B.
    Inventory control in construction projects is a key function to the project success. Inventory serves as a link between planning and execution of a project. In construction industry, majority of the cost is involved in inventories so it is important to keep the inventories under strict control otherwise it may lead to cost and time overrun. As construction industry consumes large part of inventories, so it produces huge amount of wastes. It is established that the wastages have a significant negative impact on cost and time of a project. So, it is of utmost importance to know the impact of these causes of wastages on cost and time so that a proper mitigation plan can be prepared and impact of these causes of wastage be reduced or eliminated. This paper mainly put emphasis on safety stock analysis aiming to determine the safety stock of inventories after calculation of average lead time, actual lead time, average demand per day, standard deviation and service factor from the set of data obtained from the site. It also aims to provide a model for automation of safety stocks to prevent stock-outs using PYTHON software. Apart from that, it involves a questionnaire survey to analyze the impact of various causes of wastage in construction on the basis of cost and time. © 2021, Springer Nature Singapore Pte Ltd.
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    Automation with Blockchain: Creating a Marketplace for IoT Based Irrigation System
    (Springer Science and Business Media Deutschland GmbH, 2023) Divakarla, U.; Chandrasekaran, K.
    The next revolutionary technology to emerge since the creation of bitcoin in 2008 is blockchain technology. The Internet of Things (IoT), security, and other industries have all adopted blockchain technology. The article discusses the use of smart contracts, an Ethereum blockchain feature, to automate transactions in the Ethereum blockchain-based marketplace platform for Internet of Things devices. The following is demonstrated as a proof of concept by building a prototype of the suggested platform utilising Ethereum, Ganache, Web3, and Metamask. This exemplifies how transactions can be automated using smart contracts on the blockchain. When the land’s moisture content is less than some critical value, the prototype concentrates on automating the watering of the land. Real-time monitoring of the moisture level of the consumer’s land is possible. On the basis of the centralised paradigm, attempts are being made to construct such a system. The goal is to automate every activity. In the blockchain, the smart contract functions like a living thing. Because of this, automating is made possible. The blockchain also gives each gadget a unique account, considering them as participants in the transaction rather than just the sold goods, increasing the potential for automation. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    A continuous flow microreactor as a practical tool for the synthesis of active pharmaceutical ingredients
    (Institution of Chemical Engineers, 2024) Bhaskar, K.; Rashed, M.; Bhat, K.; Lee, J.; Kim, K.-H.; Buruga, K.
    Continuous flow processing has become a key technology to maximize the capabilities of chemical syntheses. Numerous new tactics have been devised to synthesize various chemicals including active pharmaceutical ingredients (APIs) via a continuous flow system using microreactors. This review aims to illustrate the holistic system approach and diverse applications of continuous flow microreactors for the synthesis of APIs (with respect to type, design, and fabrication). This review also highlights the applicability of continuous flow microreactors in the synthesis of APIs in contrast to conventional batch-type methods along with a discussion of their merits and demerits. Overall, this review is expected to offer valuable insights into the utility of continuous flow microreactor technology for the upscaled production of commercially feasible APIs. © 2024 The Institution of Chemical Engineers
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    ZigBee based Real Time System for Environmental Parameters Monitoring in Model Mine: An Experimental Study
    (World Researchers Associations, 2025) Naik Anil, S.; Kumar, R.S.; Raj, M.G.
    The global mining industry, known for extracting valuable minerals like coal, iron ore, gold, silver, copper and zinc, primarily operates through underground mining. These underground mine environments are influenced by various environmental factors including toxic and flammable gases, increased carbon dioxide (CO2) levels and decreased oxygen (O2) concentrations. These factors significantly impact the productivity and safety of mine workers, making monitoring harmful gases crucial. Various methods exist to measure gas concentrations and respond appropriately when these levels exceed safe thresholds. However, each method has its own set of limitations. In underground mines, wireless monitoring systems are essential to monitor environmental parameters in real time. This study focuses on the assessment of ZigBee-based wireless techniques for their application in underground mines. The developed ZigBee wireless communication system was tested and validated at the surface level and in a model mine laboratory at the Mining Engineering Department of the National Institute of Technology Karnataka (NITK), Surathkal, India. This laboratory replicates an underground mine setting. The ZigBee-based system is designed to wirelessly monitor environmental parameters. Experiment results suggest that the ZigBee network is suitable for real-time monitoring of environmental conditions in underground mines. Further details regarding the functioning, effectiveness and potential applications of the ZigBee-based system in underground mining are discussed in the study. © 2025, World Researchers Associations. All rights reserved.
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    Automatic identification of diabetic maculopathy stages using fundus images
    (2009) Nayak, J.; Subbanna Bhat, P.S.; Acharya, R.
    Diabetes mellitus is a major cause of visual impairment and blindness. Twenty years after the onset of diabetes, almost all patients with type 1 diabetes and over 60% of patients with type 2 diabetes will have some degree of retinopathy. Prolonged diabetes retinopathy leads to maculopathy, which impairs the normal vision depending on the severity of damage of the macula. This paper presents a computer-based intelligent system for the identification of clinically significant maculopathy, non-clinically significant maculopathy and normal fundus eye images. Features are extracted from these raw fundus images which are then fed to the classifier. Our protocol uses feed-forward architecture in an artificial neural network classifier for classification of different stages. Three different kinds of eye disease conditions were tested in 350 subjects. We demonstrated a sensitivity of more than 95% for these classifiers with a specificity of 100%, and results are very promising. Our systems are ready to run clinically on large amounts of datasets. © 2009 Informa Healthcare USA, Inc.
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    Accurate lumen diameter measurement in curved vessels in carotid ultrasound: an iterative scale-space and spatial transformation approach
    (Springer Verlag service@springer.de, 2017) Krishna Kumar, P.; Araki, T.; Rajan, J.; Saba, L.; Lavra, F.; Ikeda, N.; Sharma, A.M.; Shafique, S.; Nicolaïdes, A.; Laird, J.R.; Gupta, A.; Suri, J.S.
    Monitoring of cerebrovascular diseases via carotid ultrasound has started to become a routine. The measurement of image-based lumen diameter (LD) or inter-adventitial diameter (IAD) is a promising approach for quantification of the degree of stenosis. The manual measurements of LD/IAD are not reliable, subjective and slow. The curvature associated with the vessels along with non-uniformity in the plaque growth poses further challenges. This study uses a novel and generalized approach for automated LD and IAD measurement based on a combination of spatial transformation and scale-space. In this iterative procedure, the scale-space is first used to get the lumen axis which is then used with spatial image transformation paradigm to get a transformed image. The scale-space is then reapplied to retrieve the lumen region and boundary in the transformed framework. Then, inverse transformation is applied to display the results in original image framework. Two hundred and two patients’ left and right common carotid artery (404 carotid images) B-mode ultrasound images were retrospectively analyzed. The validation of our algorithm has done against the two manual expert tracings. The coefficient of correlation between the two manual tracings for LD was 0.98 (p < 0.0001) and 0.99 (p < 0.0001), respectively. The precision of merit between the manual expert tracings and the automated system was 97.7 and 98.7%, respectively. The experimental analysis demonstrated superior performance of the proposed method over conventional approaches. Several statistical tests demonstrated the stability and reliability of the automated system. © 2016, International Federation for Medical and Biological Engineering.
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    A benchmark study of automated intra-retinal cyst segmentation algorithms using optical coherence tomography B-scans
    (Elsevier Ireland Ltd, 2018) Girish, G.N.; Anima, V.A.; Kothari, A.R.; Sudeep, P.V.; Roychowdhury, S.; Rajan, J.
    (Background and objectives) Retinal cysts are formed by accumulation of fluid in the retina caused by leakages from inflammation or vitreous fractures. Analysis of the retinal cystic spaces holds significance in detection and treatment of several ocular diseases like age-related macular degeneration, diabetic macular edema etc. Thus, segmentation of intra-retinal cysts and quantification of cystic spaces are vital for retinal pathology and severity detection. In the recent years, automated segmentation of intra-retinal cysts using optical coherence tomography B-scans has gained significant importance in the field of retinal image analysis. The objective of this paper is to compare different intra-retinal cyst segmentation algorithms for comparative analysis and benchmarking purposes. (Methods) In this work, we employ a modular approach for standardizing the different segmentation algorithms. Further, we analyze the variations in automated cyst segmentation performances and method scalability across image acquisition systems by using the publicly available cyst segmentation challenge dataset (OPTIMA cyst segmentation challenge). (Results) Several key automated methods are comparatively analyzed using quantitative and qualitative experiments. Our analysis demonstrates the significance of variations in signal-to-noise ratio (SNR), retinal layer morphology and post-processing steps on the automated cyst segmentation processes. (Conclusion) This benchmarking study provides insights towards the scalability of automated processes across vendor-specific imaging modalities to provide guidance for retinal pathology diagnostics and treatment processes. © 2017 Elsevier B.V.