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1 | Winter Student Research Internship Program - 2024-25 | |||||||||||||||||||||||||
2 | Sr. No. | Faculty Name | Name of the Faculty Mentor | Email ID of the Faculty Mentor | Name of the Faculty Co-mentor (Outside GUNI) | Research Area | Project Title | Project Abstract | ||||||||||||||||||
3 | 1 | Faculty of Engineering and Technology | Kamlesh Ramesh Damdoo | krd01@ganpatuniversity.ac.in | _ | Environment & Sustainability | Integrating Water Management and Landscape Design: The Transformation of Pond Areas into Ecological Zones at Ganpat University | The proposed project aims to enhance environmental sustainability at Ganpat University byrestructuring the ecological zone surrounding the existing pond near the Sewage Treatment Plant. The project involves studying the pond's current condition and developing a model fortransforming the area into an ecological zone. This zone will feature a central water body retained from the existing pond, surrounded by a walkway adorned with lush vegetation. The project seeks to create a harmonious ecosystem that promotes biodiversity, improves water quality, and enhances the aesthetic appeal of the campus. The proposed restructuring will serve as a model demonstration of sustainable landscaping practices and will be showcased as part of the university's summer internship program to inspire and educate students about environmental stewardship. | ||||||||||||||||||
4 | 2 | Faculty of Engineering and Technology | Dr. Anvita Sharma | aas03@ganpatuniversity.ac.in | _ | Renewable Energy / Waste to Energy | Synthesis and characterization of next generation Biofuel from waste materials using Solvents | In a time of steady decline in petroleum reserves, instability in oil prices, strong environmental legislation and concerns about global warming, researchers and petroleum industries are actively searching for cost-effective processes to convert renewable biomass resources into biofuels and other value-added chemicals. Greener solvents as catalysts or co-solvents have been used in a variety of applications such as organic synthesis, electrochemistry, bio-catalysis, as modification media for nanomaterials, as mobile phase modifiers in chromatography, biosensors, and many more. The research into greener solvents is comparatively in its infancy. We aim to use greener and cheaper solvents for the synthesis of biofuel. Such research can provide a sustainable approach for better alternatives to fossil fuels as well as compensate for the demand for future fuels which is going to increase drastically. | ||||||||||||||||||
5 | 3 | Faculty of Engineering and Technology | Prof H.A PATEL | himanshu.patel@ganpatuniversity.ac.in | _ | Biomedical Sciences / Healthcare | "Designing and Implementing an Intelligent Fall Detection Device for Enhanced Elderly Safety Using MicroBit" | Falls are a leading cause of injury and death among the elderly, with statistics showing that one in four older adults falls each year, and falls account for over 95% of hip fractures. Traditional fall detection systems, which often involve cumbersome wearables or stationary sensors, have limitations in accuracy and user acceptance. Recent advancements in technology, including machine learning and sensor fusion, have significantly improved detection methods. The MicroBit, a versatile and affordable single-board computer, is an ideal platform for developing these advanced systems. Our project innovatively uses the MicroBit to create a fall detection device that integrates accelerometers and gyroscopes to monitor and analyze movement patterns in real-time. The system employs machine learning algorithms to accurately differentiate between falls and normal activities, minimizing false positives and negatives. An added advantage is its Wi-Fi capability, enabling seamless remote monitoring and real-time alerts to caregivers or emergency services. This connectivity ensures rapid response and continuous oversight. By leveraging the cost-effective MicroBit and its Wi-Fi features, our solution remains affordable while offering enhanced safety and accessibility, effectively addressing the critical need for reliable fall detection technology | ||||||||||||||||||
6 | 4 | Faculty of Engineering and Technology | Prof. Umang Thakkar | urt01@ganpatuniversity.ac.in | Mr. Digant Shah | Advanced Materials / Advanced Manufacturing, AI / ML / Data Science / IoT/Cloud based Computing | Crochet Connect | The Crochet Connect project revolutionizes crocheting by integrating a multifunctional hook with features such as interchangeable sizes, a digital screen, and a built-in light for dark yarn. Accompanied by a comprehensive web application, it provides real-time error detection, pattern guidance, and wool management. The project addresses key issues like wool utilization, environmental impact, and visibility problems. By supporting local wool sellers and enhancing user experience, it aims to modernize crochet practices while promoting sustainability and job creation. The initiative also preserves traditional crafts and improves accessibility for beginners. | ||||||||||||||||||
7 | 5 | Faculty of Engineering and Technology | Prof. Umang Thakkar | urt01@ganpatuniversity.ac.in | _ | Biomedical Sciences / Healthcare | Docmedix : A Comprehensive Web Platfrm for Healthcare Management | Docmedix is a user-friendly web platform designed to enhance healthcare management by providing quick access to patient information, real-tie monitoring, and emergency alerts. The system integrates key healthcare processes, including patient history retrieval, prescription management, and dietary tracking, within a single interface. Its goal is to improve care quality by streamlining routine tasks, minimizing errors, and promoting better decision making. One of the core features is patient bed management, offering an organized view of bed assignments along with medical and personal details, ensuring efficient patient care. Medical history retrieval is securely managed through unique serial numbers, allowing doctors and nurses to access critical information on demand. | ||||||||||||||||||
8 | 6 | Faculty of Engineering and Technology | Prof. Umang Thakkar | urt01@ganpatuniversity.ac.in | _ | Tourism Empowerment | WanderLink : AI-Driven Tourist Empowerment Platform | An AI-driven platform with a multilingual chatbot for seamless ticketing, offline maps for navigation without internet, and features like nearby hotels, top tourist spots, tour guide info, and local taxi services. | ||||||||||||||||||
9 | 7 | Faculty of Engineering and Technology | Prof. Umang Thakkar | urt01@ganpatuniversity.ac.in | _ | Agricultural / Food Sciences | Agro Connection | The Agriconnect project redefines the farm-to-consumer marketplace by creating a seamless platform that directly connects farmers with consumers and wholesalers. Featuring dedicated dashboards for farmers, consumers, and wholesalers, Agriconnect offers functionalities like product listing, order tracking, and real-time communication. Integrated with an intuitive community chat and an advanced bidding platform, the project supports transparent pricing, product quality assurance, and knowledge-sharing among users. Agriconnect enhances food accessibility, promotes sustainable agricultural practices, and empowers local farmers by expanding their market reach. This initiative supports local economies, fosters community relationships, and brings fresh produce directly to consumers' tables. | ||||||||||||||||||
10 | 8 | Faculty of Engineering and Technology | Prof. Umang Thakkar | urt01@ganpatuniversity.ac.in | _ | AI / ML / Data Science / IoT/Cloud based Computing | ArtVerse | This project creates an online platform for student artists to showcase and sell their work, offering them a sustainable way to support their education. Each art piece shares a unique story, helping buyers connect with the artist’s journey. The platform builds a community that bridges aspiring creators with potential buyers, making art accessible and meaningful. | ||||||||||||||||||
11 | 9 | Faculty of Engineering and Technology | Kadiya Tejaskumar Rasikbhai | trk01@ganpatuniversity.ac.in | _ | AI / ML / Data Science / IoT/Cloud based Computing, Blockchain Technology | Crypto Wallet | New blockchain developers often face challenges in understanding how wallets work, how transactions are signed,and how to send them. This basic project aims to simplify this learning curve by allowing users to create wallet addresses, check balances, and send simple transactions on a test Ethereum network. By focusing on the fundamental aspects of wallet operations, developers can gain a solid understanding of how cryptocurrency wallets work without diving into complex backend systems. The proposed solution is a basic crypto wallet that runs entirely on the frontend, without requiring a backend server. The wallet will allow users to perform the following tasks 1. Create wallet addresses – Users will generate new Ethereum addresses. 2. Check balances – The wallet will display the balance of the user's Ethereum address on a test network (e.g., Ropsten). 3. Send simple transactions – Users can send Ethereum transactions on a test network by signing them with their wallet private key. By using tools like Ethers.js or Web3.js, users can interact with the Ethereum blockchain, and MetaMask will be used to sign transactions securely | ||||||||||||||||||
12 | 10 | Faculty of Engineering and Technology | Dr. Anvita Sharma | aas03@ganpatuniversity.ac.in | _ | Renewable Energy / Waste to Energy | Design and Simulation of the Biodiesel Process Plant using ASPEN PLUS | The biodiesel production process is extensively studied in the literature, focusing on mechanisms, modeling, and economic aspects, yet plant design remains underexplored areas. The study addressed this gap by designing a biodiesel production plant and developing a pipe network. In this study, an integration of biodiesel production plant design and simulation of continuous production of biodiesel will be investigated. A few assumptions will be made when selecting biodiesel plant materials, such as pipes, pumps, fittings, and bends. These assumptions will be based on considerations of the biodiesel fluid properties and pressure requirements. Aspen Plus software will be used to simulate the production process of biodiesel. In the simulation, the processing parameters of methanol rectification tower and biodiesel rectification tower will be optimized to provide a reliable benchmark for industrial biodiesel production. | ||||||||||||||||||
13 | 11 | Faculty of Engineering and Technology | Prof.Himanshu A.Patel | himanshu.patel@ganpatuniversity.ac.in | _ | Biomedical Sciences / Healthcare | AI-Based Model to Detect Sciatica in Patients | The Sciatic nerve, the longest nerve in the body, runs from the lower back through the buttocks and down each leg, providing essential motor and sensory functions. Sciatica Neuropathy often caused by compression or irritation due to conditions like herniated discs or spinal stenosis. Symptoms include sharp or burning pain radiating from the lower back to the leg, accompanied by numbness, tingling, or weakness. Risk factors include age, obesity, a sedentary lifestyle, and physically demanding jobs. Sciatica is a major cause of leg pain, affecting 9.9% to 25% of the population annually, with about 40% experiencing it in their lifetime. It leads to significant disability, and is a common reason for healthcare visits, with 10-15% of patients requiring surgical intervention for persistent symptoms. The diagnosis typically involves clinical examinations and imaging studies, while treatment options range from physical therapy and pain management to surgical intervention in severe cases. Untreated sciatica can lead to chronic pain, increased disability, permanent nerve damage, and mental health issues such as anxiety and depression. Moreover, limited mobility may contribute to secondary problems like obesity and cardiovascular issues. Therefore, early diagnosis is crucial to prevent these complications. Integrating Artificial Intelligence (AI) applications can significantly enhance the diagnosis of sciatica by enabling faster, more accurate assessments. By leveraging machine learning algorithms to analyze existing clinical data and MRI images, this project aims to develop an AI-driven tool that can quickly determine if leg pain results from sciatic nerve compression. This model will incorporate demographic factors and clinical features, ultimately improving patient outcomes and increasing accessibility. The integration of AI in Sciatica Nerve pain diagnosis offers substantial benefits for patients and healthcare providers, including quicker diagnoses, personalized care, and enhanced efficiency in clinical settings. | ||||||||||||||||||
14 | 12 | Faculty of Engineering and Technology | Dr. Hemanga Kumar Das | hdd03@ganpatuniversity.ac.in | _ | Biomedical Sciences / Healthcare | Bioactivity Assays of essential oil from amla plant found in the campus of Ganpat University | The demand for natural and sustainable ingredients in the cosmetics, pharmaceutical, and wellness industries is growing. Essential oils, known for their bioactive compounds, play a significant role in these sectors. However, the potential of Phyllanthus emblica (amla) in essential oil production remains underexplored despite its rich composition of bioactive compounds with antioxidant, antimicrobial, and anti-inflammatory properties. Harnessing amla's bioactive potential for essential oil production could provide an alternative to synthetic oils and contribute to sustainable natural resource utilization. | ||||||||||||||||||
15 | 13 | Faculty of Engineering and Technology | sulabh bhatt | sgb01@ganpatuniversity.ac.in | digant shah | AI / ML / Data Science / IoT/Cloud based Computing | Smart Traffic Management System based on Traffic Density | The smart traffic management system based on traffic density optimizes traffic light control by using ultrasonic sensors to detect vehicle presence and adjust signal timings dynamically. Each intersection has a set of traffic lights (red, yellow, and green) connected to the system, and four ultrasonic sensors monitor traffic density at each signal. The traffic light stays green for a minimum duration, ensuring a fair traffic flow, but can extend up to a maximum time if traffic density remains high.If no vehicle is detected by the sensor after the minimum green time, the system switches the signal to yellow and then red, advancing to the next signal. This process reduces unnecessary waiting times at intersections, improving traffic flow efficiency. The sensors continuously monitor vehicle presence, helping to adapt real-time traffic control based on current density conditions at each intersection. | ||||||||||||||||||
16 | 14 | Faculty of Engineering and Technology | Prof. Umang Thakkar | urt01@ganpatuniversity.ac.in | _ | Blockchain | Blockchain-powered Secure Decentralized Messaging Platform | This project introduces a secure, blockchain-based decentralized messaging platform that ensures robust communication privacy and security. By leveraging blockchain for decentralized message delivery and end-to-end encryption, it safeguards message integrity and confidentiality. Smart contracts manage user authentication and access permissions, while real-time monitoring detects unauthorized access attempts, enhancing the security of the messaging environment. | ||||||||||||||||||
17 | 15 | Faculty of Engineering and Technology | Prof.Himanshu A.Patel | himanshu.patel@ganpatuniversity.ac.in | _ | Biomedical Sciences / Healthcare | AI and Biomedical Approach to Speech Therapy: Enhancing Articulation in Children with Misarticulation Disorders | Many treatments are available to address misarticulation, with speech therapy or articulation therapy focusing on pronunciation and speech production. This therapy deals with a person’s ability to move the lips, tongue, teeth, and jaw to produce speech sounds, and it tracks mouth movements and posture.Misarticulation therapy is one of the most effective treatments for articulation problems, but current treatments are often provided in physical settings, which can be inconvenient. We will offer online treatment facilities through the development of various software that includes numerous therapy activities and techniques across three to four domains: Position Level: This will show the positioning of sounds. Phoneme Level: This includes initial, medial, and final positions, ensuring that all words are represented at all three levels. Picture Level: This will present pictures related to words. Correct and Incorrect Word Production: This will help individuals identify their mispronounced words. Creating this kind of app (platform) will be immensely helpful for professionals, children, and their parents. We will develop therapy roller equipment to ensure proper tongue positioning, using additive manufacturing. Additionally, we will create hardware models, such as toys, to help children learn. INNOVATION: We will provide personalized learning sessions that include different games and traditional methods for learning to speak. Users will receive tasks tailored to their percentage of speech errors. We will also enable monitoring of improvements by doctors and therapists, with progress reports displayed on-screen, using AI/ML technologies. The platform will connect therapists from different parts of the globe, providing a centralized therapy space. Additionally, we will establish a community chat where children and parents suffering from misarticulation can come together to support one another. This represents a viable business model that can easily generate revenue. Methods Used: Picture Cards Minimal Pair Cards Articulation Worksheets Flashcards Tongue Twisters Storybooks Speech Sound Games Videos and Audio Recordings Mirror Exercises Conversation Cards Speech Sound Stories Progress Tracking Sheets By connecting therapists from around the world and creating a supportive community for children and parents, we aim to address misarticulation effectively. Technologies Used: HTML, CSS, JavaScript, Machine Learning (ML), UI/UX, MySQL, Audio and Video Editing, Graphic Design. Solution: By using the above-mentioned technologies, we will provide a solution to address misarticulation. We are the solution. | ||||||||||||||||||
18 | 16 | Faculty of Engineering and Technology | Dr. Rajesh Bhosale | dean.research@ganpatuniversity.ac.in | _ | Nanotechnology, Fluorescent Materials | Nanotechnology and Fluorescent Materials through the Lens of Indian Knowledge Systems: Merging Mythology with Modern Science | This project will investigate the integration of Indian knowledge systems with the understanding of modern science with special emphasis on nanotechnology and fluorescent materials. The project will study the fluorescent compounds historically present in ancient Indian textiles, medicines and art. Natural dyes derived from plants like Manjistha, Turmeric, Indigo, and Lac exhibited fluorescence under UV light, enriching the vibrancy and longevity of ancient miniature paintings and cave temple murals, such as those found in Ajanta and Ellora. Ancient Indian scripts, e.g. the Ramayana and other mythological literature provide references to advanced technologies used at that time like the Pushpaka Vimana (a flying chariot) and divine weapons (Astras) during the wartimes. Through the perspective of modern science, it may be presumed that there used to exist not only the advanced understanding of nanomaterials and fluorescence but also their different applications. These references encourage us to further investigate the science and techniques utilized in those times and integrate with modern science. This will require potential parallels with contemporary nanoscience and fluorescence systems to bridge the gaps. By exploring these gaps, this project aims to identify the technological and scientific achievements of ancient India, contributing to a deeper understanding of how traditional knowledge systems can inform and inspire modern scientific research in the domain of nanotechnology and fluorescence. | ||||||||||||||||||
19 | 17 | Faculty of Computer Application | Dr. Sachin A. Goswami | sag02@ganpatuniversity.ac.in | _ | Drone / Robotics Technology | Drone-based Rogue Access Point Detection and Mitigation | In today's wireless world, security challenges have increased significantly, particularly with rogue access points (RAPs) that can be used by attackers to intercept sensitive data or disrupt services. Traditional methods for detecting RAPs are often limited in their coverage and are not easily scalable. This project aims to create a drone-based system that can detect and neutralize rogue access points in real-time. By equipping drones with Wi-Fi sniffing technology and using machine learning algorithms, we can efficiently and automatically scan large areas to detect unauthorized access points and help protect networks in various settings, such as universities, offices, and government buildings. | ||||||||||||||||||
20 | 18 | Faculty of Computer Application | Dr. Meghna Patel | meghna.patel@ganpatuniversity.ac.in | AI / ML / Data Science / IoT/Cloud based Computing | Revolutionizing Agricultural Health: Machine Learning Techniques for Early Plant Disease Detection | Plant diseases are responsible for around 40% of global crop losses worldwide each year, which carries an economic cost ranging from $220 billion. Conventional detection techniques are relatively slow and inaccurate and lead to seamless propagation of the disease. Machine Learning and Deep Learning vital for the development of fast, precise plant disease detection has an ace up their sleeve to overcome existing challenges as they can match the accuracy at which plant images are analyzed against its symptoms. This allows for early intervention saving crops and making agricultural practices more efficient. It skims the essential ML and DL methods, including supervised learning and deep neural networks to increase accuracy and efficiency of detection. It promoted the implementation needs, such as well curated data, appropriate imaging and solid computational power. Such information will assist researchers and industry operators to gain insight for understanding ML and DL techniques that can pave the way for reforming plant health management, empirical recommendations are discussed here so as to mitigate practical barriers in it. | |||||||||||||||||||
21 | 19 | Faculty of Computer Application | Dr. Meghna Patel | meghna.patel@ganpatuniversity.ac.in | AI / ML / Data Science / IoT/Cloud based Computing | Multispeaker Recognition and Summarization System for Group Discussions | This project aims to develop an advanced Multispeaker Recognition and Summarization System for Group Discussions, utilizing speech recognition, speaker identification, and natural language processing (NLP) techniques. The system will address the challenge of identifying whether one or multiple participants are speaking during a group discussion, recognize individual speakers, and provide a concise summary of the discussion. Key components include Voice Activity Detection (VAD) to detect speech segments, Speaker Diarization and Recognition to differentiate speakers, Automatic Speech Recognition (ASR) for transcription, and NLP-based Summarization to provide speaker-specific summaries. The project will leverage existing machine learning models and frameworks like pyAudioAnalysis, pyannote-audio, and Hugging Face Transformers to create an integrated solution. This system will be useful for analyzing group discussions, meetings, and conferences, helping to improve accessibility, information retrieval, and content summarization. | |||||||||||||||||||
22 | 20 | Faculty of Agriculture, Allied Sciences & Technology | Trivima Sharma | tss01@ganpatuniversity.ac.in | N/A | Agricultural / Food Sciences | Boosting Iron Absorption: A Nutrient-Rich Fermented Beverage for Anemia Relief | Iron-deficiency anaemia (IDA) continues to be a significant public health challenge in India, notably affecting women and children. Recent data from the National Family Health Survey (NFHS-5, 2022) indicate a rising trend in anaemia cases across various states and union territories, highlighting an urgent need for effective solutions. In response, the Indian government launched the Anaemia Mukt Bharat (AMB) initiative in 2018, aimed at enhancing holistic health interventions for these vulnerable groups. Despite ongoing government efforts focusing primarily on iron supplementation, there is an increasing interest in exploring natural dietary strategies to improve iron bioavailability. This study introduces an innovative health drink formulated with naturally iron-rich ingredients intended to increase iron absorption. The drink comprises beetroot, pomegranate, spinach, mint, coriander, amla, and dried dates. These ingredients were specifically chosen for their nutritional properties; beetroot and pomegranate are selected for their substantial iron content and antioxidants, which play crucial roles in red blood cell production and enhancing iron absorption. Spinach contributes additional iron, while mint, coriander, and amla, rich in vitamin C, are known to boost non-heme iron absorption. The inclusion of dried dates not only imparts natural sweetness but also provides essential nutrients that support energy metabolism. Moreover, the proposed health drink will undergo a fermentation process to further augment its nutritional benefits. Fermentation is anticipated to increase nutrient bioavailability, enhance digestion, and introduce beneficial probiotics that improve gut health factors critical for optimizing iron absorption. In this investigation, we will prepare and evaluate the nutritional content and efficacy of this health drink. These trials aim to assess its potential as a daily dietary supplement for individuals prone to iron deficiency, making it a promising, natural alternative for the management and prevention of anaemia. This approach represents a proactive, innovative solution to combat the widespread issue of anaemia, aligning with the goals of the AMB strategy and contributing to the broader public health discourse. | ||||||||||||||||||
23 | 21 | Faculty of Agriculture, Allied Sciences & Technology | Dr. Hiral M. Patel | hmp05@ganpatuniversity.ac.in | _ | Agricultural / Food Sciences | Economic analysis of growth, instability and supply response of major crops in North Gujarat | This study offers a detailed economic analysis of growth, instability and supply response of major crops in North Gujarat, a region vital to India’s agricultural output due to its arid climate and diverse cropping patterns. Utilizing econometric models, the research examines the growth rates of key crops such as cotton, wheat and groundnut over the past two decades, revealing trends and variations in productivity. The analysis highlights significant volatility in crop production, driven by factors like climatic variability, market fluctuations, and policy changes, which poses challenges for both farmers and policymakers. The study employs statistical measures to assess this instability, demonstrating the impact of external variables on crop yields. Furthermore, the research evaluates how supply responses of these crops to price changes and input costs inform farmers' decisions. By applying supply response models, the study uncovers how farmers adjust their resource allocation based on relative price shifts, offering insights into their decision-making processes. By integrating growth rates, instability, and supply responses, the findings identify key determinants influencing agricultural performance in North Gujarat. Recommendations include enhancing irrigation practices, improving access to market information and promoting sustainable agricultural methods. Overall, this analysis not only contributes to the literature on agricultural economics in India but also provides actionable insights for enhancing productivity and sustainability in North Gujarat’s farming sector, underscoring the importance of economic analysis in shaping effective agricultural policy. | ||||||||||||||||||
24 | 22 | Faculty of Agriculture, Allied Sciences & Technology | Dr. Deepak Sharma | dds02@ganpatuniversity.ac.in | _ | Agricultural / Food Sciences | Elucidating evolutionary diversity of Heat Shock Protein in Poaceae family | Heat shock proteins (HSPs) play critical roles in regulating different mechanisms under high-temperature conditions. HSPs have been identified and well-studied in different plants. The grass family Poaceae includes annual species cultivated as major grain crops and perennial species cultivated as forage or turf grasses. Heat stress is a primary factor limiting growth and productivity of cool-season grass species and is becoming a more significant problem in the context of global warming. Plants have developed various mechanisms in heat-stress adaptation, including changes in protein metabolism such as the induction of heat shock proteins (HSPs). According to the size and structure of proteins, HSP family members are divided into five groups, namely HSP100, HSP90, HSP70, HSP60, and sHSP, involved in various aspects of cellular function. The study focused on the evolutionary aspect of the HSPs and their diversity among the cereals and grasses helps in understating the relation and targeting the various HSPs to study heat tolerance in plant. | ||||||||||||||||||
25 | 23 | Faculty of Agriculture, Allied Sciences & Technology | Dr. Deepak Sharma | dds02@ganpatuniversity.ac.in | _ | Agricultural / Food Sciences | Standardizing Protocols for In Vitro Screening of Drought Tolerance in Wheat Genotypes | This study aims to develop and standardize protocols for the in vitro screening of drought tolerance in various wheat genotypes. As global climate change intensifies water scarcity, enhancing drought resilience in wheat is critical for food security. We evaluated multiple genotypes under controlled in vitro conditions, assessing physiological and biochemical parameters such as germination rates, root length, and osmotic potential. By establishing consistent methodologies, including growth media composition and environmental conditions, we ensured reproducibility and reliability of results. The standardized protocols enable the identification of promising drought-tolerant genotypes, facilitating targeted breeding efforts. This work lays the foundation for future research in crop improvement and contributes to sustainable agricultural practices in water-limited environments | ||||||||||||||||||
26 | Faculty of Science | Dr Keyur Bhatt | kdb01@ganpatuniversity.ac.in | Pranav S Shrivastav | Nanotechnology, | Metal Nanoparticle Sensors for Detecting Environmental Toxins: Applications in Bioremediation Strategies | Toxin detection in the environment is essential for protecting public health and ecosystems. For the detection of a variety of environmental contaminants, such as heavy metals, pesticides, and organic poisons, metal nanoparticles (MNPs) have become extremely sensitive and selective sensors. The production, functionalization, and use of metal nanoparticle sensors for environmental toxin detection are examined in this review. Even at trace amounts, MNPs like gold, silver, and platinum may be quickly and accurately detected thanks to their special optical, electrical, and catalytic characteristics. Additionally, combining them with bioremediation techniques provides a sustainable method of managing pollution, since MNPs can act as catalysts and detectors in the detoxification of toxic compounds. Recent developments in MNP-based sensing technologies, their use in real-time environmental monitoring, and the possibility of integrating these sensors with biological systems for improved bioremediation are highlighted in this research. Future research will concentrate on increasing sensor sensitivity, cutting production costs, and creating multipurpose platforms that can identify, break down, and eliminate environmental pollutants all at once. | |||||||||||||||||||
27 | Faculty of Science | Dr. Ajay Kumar Gupta | director.research@ganpatuniversity.ac.in | _ | Nanotechnology, Waste-water treatment | Innovative Dendritic Polymers based nanomaterials for waste-water treatment: solving Social and Environmental Challenges | Water-soluble dendrimers, highly branched macromolecules with wellregulated size and structure, hold great potential in environmental and medicinal applications. Their water solubility is achieved by incorporating hydrophilic groups, with synthesis methods such as divergent and convergent approaches influencing their structure and scalability. Dendrimers are utilized in pollutant degradation, heavy metal removal, water purification, imaging, and gene therapy. This research explores dendrimer types, their properties, and applications in both environmental and medical fields. Additionally, functionalized iron oxide nanoparticles (IONPs) with dendrimers offer a promising solution for water treatment by enhancing adsorption and desalination efficiency, though challenges remain in scaling these technologies for industrial use. By leveraging the large surface area, high reactivity, and magnetic properties of these nanoparticles, they can efficiently adsorb and remove contaminants, leading to improved desalination and water quality. Recent advancements in nanomaterials have enhanced their performance in reducing TDS and hardness, offering a sustainable and cost-effective alternative to traditional desalination methods. This technology will be developed to address social and environmental challenges related to clean and potable water | |||||||||||||||||||
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