Research Publications

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    Development of pH value detection sensor for water to detect and automate water neutralization process
    (International Journal of Research and Analytical Reviews(IJRAR), 2022-06) Ganesh Ram, V.; Aravind, D.
    Water pollution is one of the severe problems that have crippling effect on public hygiene. This paper proposes a suitable method to detect and perform corrective measures using sensing components to aid maintenance of water quality. In the money conservative market like India, less importance is given for public hygiene and there is a general myth that any quality monitoring system would be costly and complex in its operation. Water is a universal solvent and in nature, it is never totally pure. No matter how for isolated, it is from sources of contamination, it will always have some chemicals. Gases or minerals in the air, soil, or rock are dissolved by the water. Some dissolved materials give water its characteristic taste, and “pure water” is generally considered to be flat and tasteless. Our main purpose is to identify and treat to remove unwanted constituents in the water and to make it safe or fit for a specific purpose in industry or domestic applications. We are making our system portable and compact, to process only upto a certain limit as it is a prototype. The development of pH electrode plays a major role for this research. Resistance is measured for various levels of water, where non-linear resistance identifies the pH value. Each individual liquid has a different resistance level for the pH. As resistivity is directly proportional to the current & voltage. The methodology presents a self-developed pH level indicator that measures pH level of the water. The end process gives quality water for people usage and indicates the same with its auto monitoring system.
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    Real time implementation of home energy management
    (Journal of Survey in Fisheries Sciences, 2023) Thangalakshmi, S.; Sivasami, K.
    Automation is the key word in every industry. Automation is essential to obtain the desired response much faster than the conventional methodologies. It ensures efficiency and increase in production and reduces human errors. The optimal goal of this project is to obtain a bi directional data communication by using the existing power lines. Here the energy consumed by the user is continuously measured and updated. At the end of the billing period, it can be received by the electricity board office on request. A processor IC senses the energy consumed, produces a digital pulse accordingly and displays the amount of energy consumed. These pulses are suitably modulated by the MODEM and superimposed along with the same power line. These pulses are alone retrieved at the electricity board’s office by the other MODEM and stored in the PC database. The tariffs are calculated based upon the slabs fed in the PC and sent through the modem which is received by the other modem. The LCD provided displays the number of units consumed and the cost. In this project, along with the automatic meter reading two more important things are implemented, they are power on demand and prepaid system with recharging facility.
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    Machine learning methods for marine systems
    (IOP Conference Series: Materials Science and Engineering, 2021) Thangalakshmi, S.; Sivasami, K.
    Automation plays a key role in shipping industry and aims towards minimal operating staff. However, the effective automation relies on effective controlling at various levels starting from shipbuilding to navigation. The industry is currently focussing on autonomous shipping which actually requires precise controlling. Although many conventional methods are available for control and automation with regard to automation, Artificial Intelligence Schemes (AIS) are widely attracting the maritime sector because of their benefits. The AIS along with fuzzy logic systems are offering promising results. The emerging use of AIS in a variety of maritime applications can act as a reference wpoint for new researchers. This paper aims to conduct a valid AIS study and to examine the various machine learning approaches used in various maritime applications. It is possible to achieve complete automation in the shipping industry by implementing a related technique.