Zion Ramdinthara | Pondicherry university (original) (raw)

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Papers by Zion Ramdinthara

This book contains abstracts of the various research papers of the academic & research co... more This book contains abstracts of the various research papers of the academic & research community presented at the International Conference on Innovations and Challenges in Computing, Analytics and Security (ICICCAS-2020). ICICCAS-2020 has served as a platform for researchers, professionals to meet and exchange ideas on computing, data analytics, and security. The conference has invited papers in seven main tracks of Data Science, Networking Technologies, Sequential, Parallel, Distributed and Cloud Computing, Advances in Software Engineering, Multimedia, Image Processing, and Embedded Systems, Security and Privacy, Special Track (IoT, Smart Technologies and Green Engineering). The Technical and Advisory Committee Members were from various countries that have rich Research and Academic experience. Conference Title: TEQIP - III Sponsored First International Conference on Innovations and Challenges in Computing, Analytics and SecurityConference Acronym: ICICCAS-2020Conference Date: 29-30 July 2020Conference Location: Pondicherry Engineering College, Puducherry – 605014, India (Virtual Mode)Conference Organizer: Department of Computer Science and Engineering, Pondicherry Engineering College, Puducherry, India.Conference Sponsor: TEQIP-III NPIU (A Unit of the Ministry of Human Resource Development, India)

International Journal of Advanced Computer Science and Applications

The need for instantaneous processing for Internet of Things (IoT) has led to the notion of fog c... more The need for instantaneous processing for Internet of Things (IoT) has led to the notion of fog computing where computation is performed at the proximity of the data source. Though fog computing reduces the latency and bandwidth bottlenecks, the scarcity of fog nodes hampers its efficiency. Also, due to the heterogeneity and stochastic behavior of IoT, traditional resource allocation technique does not suffice the timesensitiveness of the applications. Therefore, adopting Artificial Intelligence (AI) based Reinforcement Learning approach that has the ability to self-learn and adapt to the dynamic environment is sought. The purpose of the work is to propose an Auto Centric Threshold (ACT) enabled Monte Carlo FogRA system that maximizes the utilization of Fog's limited resources with minimum termination time for time-critical IoT requests. FogRA is devised as a Reinforcement Learning (RL) problem, that obtains optimal solutions through continuous interaction with the uncertain environment. Experimental results show that the optimal value achieved by the proposed system is increased by 41% more than the baseline adaptive RA model. The efficiency of FogRA is evaluated under different performance metrics.

International Journal of Advances in Agricultural Science and Technology

Agriculture and global warming are correlated with each other, particularly, it may affect nutrie... more Agriculture and global warming are correlated with each other, particularly, it may affect nutrient cycles, microbial activities, and physiological activities of the crops. Agricultural development plays a crucial role in the growth of the economy of developing countries. The agriculture sector is a major source of employment in most of the developing countries. Over the year, there were changes and productivity loss due to the abiotic stresses and imbalance of nutrients of the plants. A continuous increase in temperature may affect the yields of crops up to 17%. Each plant has different characteristics in growth and some plants are susceptible to high temperature, some are quite the opposite. A Brassica Juncea L. belongs to a mustard family Brassicaceae or Cruciferae that are susceptible to high temperature. So, in this work, an attempt has been made for Brassica Juncea L. to grow and yield under temperature stress by controlling the temperature with the use of the Internet of Thin...

AIJR Abstracts, Jul 29, 2020

International Journal of Advanced Computer Science and Applications, 2021

The voluminous data produced and consumed by digitalization, need resources that offer compute, s... more The voluminous data produced and consumed by digitalization, need resources that offer compute, storage, and communication facility. To withstand such demands, Cloud and Fog computing architectures are the viable solutions, due to their utility kind and accessibility nature. The success of any computing architecture depends on how efficiently its resources are allocated to the service requests. Among the existing survey articles on Cloud and Fog, issues like scalability and time-critical requirements of the Internet of Things (IoT) are rarely focused on. The proliferation of IoT leads to energy crises too. The proposed survey is aimed to build a Resource Allocation and Service Placement (RASP) strategy that addresses these issues. The survey recommends techniques like Reinforcement Learning (RL) and Energy Efficient Computing (EEC) in Fog and Cloud to escalate the efficacy of RASP. While RL meets the time-critical requirements of IoT with high scalability, EEC empowers RASP by saving cost and energy. As most of the early works are carried out using reactive policy, it paves the way to build RASP solutions using alternate policies. The findings of the survey help the researchers, to focus their attention on the research gaps and devise a robust RASP strategy in Fog and Cloud environment.

Research Anthology on Food Waste Reduction and Alternative Diets for Food and Nutrition Security, 2021

Sustainable agriculture helps to promote farming practices and methods in order to sustain farmer... more Sustainable agriculture helps to promote farming practices and methods in order to sustain farmers and resources. It is economically viable, socially supportive, and economically sound. It assists to maintain soil quality, reduce soil erosion and degradation, and also save water resources. Sustainable agriculture improves the biodiversity of the land and thus leads to the healthy and natural environment. The sustainable agriculture is very essential to ordinate with the increasing demand for the food, climate change, and degradation of the ecosystem in future. It plays a major role for preserving natural resources, reducing greenhouse gas emissions, halting biodiversity loss, and caring for valued landscapes. Sustainable agriculture is applied to farming in order to preserve the nature without compromising the quality of the future generation basic needs and thus enable to make smartness in farming. The common practices included in smart farming for sustainable agriculture are crop ...

The Smart Cyber Ecosystem for Sustainable Development, 2021

<jats:p>Deep learning models can achieve more accuracy sometimes that exceed human-level pe... more <jats:p>Deep learning models can achieve more accuracy sometimes that exceed human-level performance. It is crucial for safety-critical applications such as driverless cars, aerospace, defence, medical research, and industrial automation. Most of the deep learning methods mimic the neural network. It has many hidden layers and creates patterns for decision making and it is a subset of machine learning that performs end-to-end learning and has the capability to learn unsupervised data and also provides very flexible, learnable framework for representing the visual and linguistic information. Deep learning has greatly changed the way and computing devices processes human-centric content such as speech, image recognition, and natural language processing. Deep learning plays a major role in IoT-related services. The amalgamation of deep learning to the IoT environment makes the complex sensing and recognition tasks easier. It helps to automatically identify patterns and detect anomalies that are generated by IoT devices. This chapter discusses the impact of deep learning in the IoT environment. </jats:p>

Studies in Big Data, 2019

This chapter presents different techniques and applications of Artificial Intelligence for yield ... more This chapter presents different techniques and applications of Artificial Intelligence for yield prediction and smart irrigation. Timely prediction of irrigation requirements and crop yields is necessary for farmer’s welfare and satisfaction. The beforehand prediction significantly contributes to minimizing production cost and maximizing crop yields. The precise prediction of crops’ yields is also useful for government, as it is effective in planning various schemes, transport needs, buying mechanisms, storage infrastructure, and liquid position of the economy before actual selling of crop by farmers to market. This chapter acknowledges the past breakthroughs and emerging Artificial Intelligence-based techniques in precision farming specifically for yield prediction and smart irrigation. Artificial Intelligence-based system provides sufficient information about crop yields at an early stage and its associated smart irrigation management system is effective in the judicious use of essential resources such as water and energy for agriculture.

2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)

Agriculture is the backbone of every country. It produces all the necessary needs such as wheat, ... more Agriculture is the backbone of every country. It produces all the necessary needs such as wheat, rice, fruits, grains which are consumed by a human for everyday survival. So, it is important for the country to develop and sustain a productive agricultural system. As demand is increasing for food, food security is very important to sustain and increase yield production at a higher rate and at the same time preserve the ecosystem. So, the technologies in the agricultural domain may be incorporated to enhance food supplies and production. In many countries like the USA, China and Israel have a prominently high implementation of technologies with a high rate of food production and even exported in many parts of the world. These countries have implemented advanced techniques such as the Internet of Things (IoT), Cloud Computing, Machine Learning and Deep Learning algorithm for agriculture domain. Sensor technology used in this domain is highly effective, accurate and productive for precision agriculture. In this topic, agriculture in some developed and developing countries are compared also discusses the way in which these countries could possibly exchange feasible ideas from a different perspective for the development of sustainable agriculture.