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In a groundbreaking collaboration, Dr Banee Bandana Das, Assistant Professor in the Department of Computer Science and Engineering, and Dr Saswat Kumar Ram, Assistant Professor in the Department of Electronics and Communication Engineering, have joined forces with Btech-CSE students Mr Rohit Kumar Jupalle, Mr Dinesh Sai Sandeep Desu, and Mr Nikhil Kethavath to develop and patent an innovative invention.,” The team’s invention, titled “A SYSTEM FOR VISION-BASED INTELLIGENT SHELF MANAGEMENT SYSTEM AND A METHOD THEREOF,” has been officially filed and published with Application Number 202441039394 in the Patent Office Journal. This invention showcases the academic excellence and collaborative spirit within the institution, as faculty members and students work together to push the boundaries of technology and create solutions with real-world impact.
This significant achievement not only highlights the creativity and dedication of the individuals involved but also underscores the institution’s commitment to fostering a culture of innovation and research. The publication of this invention paves the way for further exploration and development in the field of intelligent shelf management systems, demonstrating the potential for transformative contributions to the industry.

Abstract
This research offers the best solution to improve the business in the retail realm, maintaining On- Shelf Availability (OSA) is vital for customer satisfaction and profitability. Traditional OSA methods face accuracy challenges, prompting a shift to deep learning models like YOLO and CNN. However, data quality remains a hurdle. This research introduces OSA, a novel semi-supervised approach merging ’semi-supervised learning’ and ’on-shelf availability’ with YOLO. It reduces human effort and computation time, focusing on efficient empty-shelf detection. Implementing a Vision-Based Intelligent Shelf Management System empowers retailers with real-time insights, revolutionizing decision-making. The model is optimized for diverse devices and provides practical solutions for efficient retail operations. Balancing model complexity, size, latency, and accuracy, the research paves the way for an advanced, data-driven shelf management approach, contributing to improved shopping experiences and business profitability

Practical Implementation and the Social Implications Associated
1. The present invention is a time-saving method in maintaining the stocks.
2. The use Vision-Based Intelligent Shelf-Management System provide a well alternative in reducing the labor efforts.
3. The system will help in terms of self-management system using machine learning techniques to optimize restocking decisions.
The present invention can be used in shopping malls and business areas for enhancing customer experiences and business and few application areas are:
• Smart City and smart Village
This technique and system can reduce the human efforts in identifying vacant slots for items in business areas and provides necessary inputs to fill the same within a time frame.
• Automobile Industry
The system can be easily integrated with the showrooms to identify the empty spaces and inform to get it fill with products.

Collaborations
SRM AP Faculties and UROP Students

Future research plan

In the future, different deep learning and machine learning methods can be merged to explore better performance in identifying overlapping objects.

The Department of Electrical and Communication Engineering at SRM University-AP is delighted to announce the publication of a patent by its faculty, including Associate Professor Dr Pradyut Kumar Sanki and Assistant Professor Dr Swagata Samanta, along with research scholars Ravisankar Dakupati, Syed Ali Hussain, and P N S B S V Prasad V. The patent, titled “Method and Apparatus for Safeguarding Livestock Near Railway Tracks using Non-Lethal Deterrent Technology,” has introduced a groundbreaking solution that helps prevent accidents of wandering cattle. This innovative technology promises to protect livestock and minimise economic losses for cattle owners while championing the advancement of technology in countries like India.

Abstract:

Nowadays we have been hearing that Vandebharat express train hits cow, causing damage to both railways and cattle owners. We need to find a solution to this problem. These issues shouldn’t be hurdle for the growth of technology for developing countries like india. The technology we are going to use is a belt is worn by a cow. When the cow tries to cross near railway track it receives a Non-Lethal shock, makes the cow to scare and move back. All this circuit is operated with 7.4V DC

Practical implementation:

The practical implementation of the Anti-Track Cattle Band involves equipping cows with the device to prevent accidents near railway tracks. By detecting magnetic fields and delivering non-lethal shocks, the device ensures the safety of both the cattle and the railway infrastructure. This implementation can significantly reduce the risk of collisions and protect valuable livestock.
From a social perspective, the invention has several implications. It addresses the safety concerns of both animals and humans by preventing accidents and minimizing potential harm. By safeguarding livestock near railway tracks, the technology contributes to animal welfare and reduces economic losses for cattle owners. Additionally, the device promotes a more humane and proactive approach to mitigating risks associated with animal-human interactions in railway environments.

Collaborations:

The research on the Anti-Track Cattle Band involved collaboration among a team of inventors with diverse expertise:
Ravisankar Dakupati – Research Scholar at SRM University-AP
Salvendar Kovelakar – Software Engineer at DXC Technology, Bangalore
Syed Ali Hussain – Research Scholar at SRM University-AP
P N S B S V Prasad V – Research Scholar at SRM University-AP
Dr Pradyut Kumar Sanki – Associate Professor at SRM University-AP
Dr Swagata Samanta – Assistant Professor at SRM University-AP
This collaborative effort brought together individuals with backgrounds in research, software engineering, and academia to develop and implement the innovative Anti-Track Cattle Band technology.

Future Research Plans:

In future research for patent publication regarding “Apparatus and Method for Railway Livestock Protection,” the focus will likely be on enhancing sensor technology to detect animals more accurately over longer distances and in various conditions. This could involve integrating artificial intelligence and machine learning for improved detection and reducing false alarms. Additionally, there may be efforts to develop systems for remote monitoring and control, enabling real-time adjustments from a central location. Adaptability to different environments, collaboration for standardized protocols, cost-effectiveness, and assessing environmental impacts will also be key areas of interest. Overall, future research aims to create more effective, efficient, and sustainable solutions for protecting livestock around railway tracks

 

Dr Pradyut Kumar Sanki, Dr Swagata Samanta, and research scholar Ms Pushpavathi Kothapalli from the Department of Electronics and Communication Engineering published their patent titled “A Kidney Abnormality Detection System And a Method Thereof,” with Application No. 202441040616. This innovative method, which utilises advanced deep learning techniques, promises to revolutionise the accuracy and efficiency of kidney disease diagnosis. With the potential for widespread clinical adoption, this technology aims to enhance patient care, offering a brighter future for kidney disease detection and treatment.

Abstract:

This research work aimed to develop a method for detecting kidney diseases, including kidney stones, cysts, and tumors. The method achieved high accuracy in detecting kidney diseases, with a good mean average precision, precision, and recall. The study used techniques to select the most relevant features for kidney disease detection, identifying top features related to blood tests and patient health. The method outperformed other approaches in terms of accuracy, precision, and recall. The study used a comprehensive dataset of kidney disease patients to train and test the method. The results suggest that the method has the potential to be widely adopted in clinical settings, contributing to more accurate and efficient diagnostic tools for kidney disease detection and improving patient care.

Practical implementation:

The practical implementation of our research involves deploying a system for real-time detection and classification of kidney disease, including kidney stones, cysts, and tumors. The method achieved high accuracy in detecting kidney diseases using the Deep learning technique. Our model can quickly identify the disease of the kidney. The study used techniques to select the most relevant features for kidney disease detection, identifying top features related to blood tests and patient health. The method outperformed other approaches in terms of accuracy, precision, and recall. The study used a comprehensive dataset of kidney disease patients to train and test the method. The results suggest that the method has the potential to be widely adopted in clinical settings, contributing to more accurate and efficient diagnostic tools for kidney disease detection and improving patient care.

Future Research Plans:
The future plans for the work on chronic kidney disease (CKD) detection and management involve several key areas:

1. Improved Screening and Diagnosis: Update the United States Preventive Services Task Force (USPSTF) recommendation for CKD screening to reflect current evidence supporting routine screening for high-risk asymptomatic adults.

2. Enhanced Patient Engagement and Person-Centered Care: Advance education of primary care clinicians about CKD risk factors, testing, detection, and interventions that are graded and proportional to the eGFR and uACR risk stratification or heat map.

3. Advancements in Nephrology: Develop novel therapeutic strategies, such as wearable artificial kidneys, xenotransplantation, stem cell-derived therapies, and bioengineered and bio-artificial kidneys, to improve renal replacement therapies and address the shortage of kidney donors.

4. Machine Learning and Predictive Modelling: Continue to evaluate and improve machine learning approaches for early CKD diagnoses, focusing on reducing the number of input features and enhancing the accuracy of prediction models.

 

 

Dr Basu Pens a Book on Life's BoulevardIn the esteemed corridors of academia, where the pursuit of knowledge intertwines with the art of mentorship, Dr Srabani Basu emerges as a figure of inspiration and innovation. Nestled within the vibrant community of SRM University-AP. Dr Basu is not just an Associate Professor in the Department of Literature and Languages, but a beacon of intellectual and administrative prowess. Her recent publication, A Mosaic of Thoughts: A Journey Through Life’s Boulevard, is a book of 12 insightful articles that recount interesting snippets of life and experiences both in Academia and Corporate.

Abstract:

Dive into “Mosaic of Thought,” a captivating collection of 12 insightful articles exploring the intricacies of contemporary life. This book challenges conventional thinking with themes such as “Are We Manufacturing Countless Bricks in the Wall?” questioning conformity in education and society, and “Of Apes, Leaders, and Organisations,” delving into the primal roots of leadership. Navigate learning complexities in “Is Your Map Meeting Your Learner’s Map?” and confront harassment in “Bullies of All Colours.” Discover the culture of blame in “Blame is the Name of the Game,” and re-imagine cartoons with “Re-discovering Tom and Jerry Through a Quantum Lens.” Each article offers unique perspectives, from fleeting moments in “The Irreplaceable Moments Explored” to impactful first impressions in “Of Halos and Horns.” With humour and seriousness, “A Comedy of Ctrl C and Ctrl V” critiques digital originality, while “Echoes of Influence: A Caveat” warns of the impact of words. This collection is a thought-provoking mosaic for understanding the multifaceted canvas of life.

About the Author:

Dr Srabani Basu, with a distinguished career spanning over 29 years, is an accomplished academic and corporate trainer. Currently serving as an Associate Professor in the Department of Literature & Languages at SRM University, A.P., she has an extensive background in education and training. Dr Basu earned her PhD in English from IKSVV (India’s first Music & Fine Arts University) in Chhattisgarh, India, in 2003. She also holds a PGDBM in Public Relations from Bhavan’s College of Communication & Management, Kolkata, and an MS in Psychoanalysis from IPMS, Mumbai, with a specialization in Students’ Psychology.

Dr Basu has held significant roles as a senior corporate trainer, master coach, content developer, and organisation development specialist. Her experience includes training across diverse industries such as media, banking, telecom, IT, ITES, engineering, FMCG, manufacturing, and education. Her expertise lies in delivering life – skills solutions and providing qualitative improvements. With a profound understanding of human psychology, Dr Basu excels in creating engaging and effective training and classroom sessions that empower participants and students in fostering individual creativity.

In addition to her academic and training roles, Dr Basu is a certified Career Transition Coach, a Neuro-Linguistic Programming (NLP) Master Practitioner, and a Gestalt Master Practitioner. She adeptly customizes her content to match the experience level and knowledge of her target audience and often integrates insights from multiple disciplines to provide holistic learning for the learners. She strongly believes that “Our ambition should be to rule ourselves, the true kingdom for each one of us; and true progress is to know more, and be more, and to do more.”

We wish her all the best for her book and hope for many more to come.

For more details:
https://notionpress.com/read/a-mosaic-of-thoughts?book=published&utm_source=share_publish_email&utm_medium=email

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