Khongdet Phasinam

@psru.ac.th

Assistant Professor of Agricultural and Agro-Industry Engineering, Faculty of Food and Agricultural Technology
Pibulsongkram Rajabhat University

Khongdet Phasinam


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Dr. Khongdet Phasinam is an accomplished Senior Lecturer in Agricultural and Food Engineering, currently serving as an Assistant Professor in Agricultural and Agro-Industry Engineering, and Vice Dean at the Faculty of Food and Agricultural Technology at Pibulsongkram Rajabhat University, Thailand. He obtained his academic qualifications from Suranaree University of Technology, Thailand, consisting of a B.Eng. degree in Agricultural Engineering, an M.Eng. degree in Energy Management Engineering, and a Ph.D. degree in Agricultural and Food Engineering. Dr. Phasinam has a cumulative experience of 18 years in Teaching, Research, and Industry. His research interests revolve around various areas, including but not limited to, Measurement and Instrumentation in Agriculture, Machine Learning, Precision Agriculture, and Internet of Things (IoT).

EDUCATION

Ph.D. (Agricultural and Food Engineering)
M.Eng. (Energy Management Engineering)
B.A. (Information Science)
B.Eng. (Agricultural Engineering)

RESEARCH, TEACHING, or OTHER INTERESTS

Engineering, Mechanical Engineering, Agricultural and Biological Sciences, Energy Engineering and Power Technology
68

Scopus Publications

Scopus Publications

  • The lopsided effects of educational trends on quality education for UN SDG achievement: A case study of neurodiverse and marginalised groups
    Dowroong Watcharinrat, Innocent Chimankpa Mbadike, Pradit Songsangyos, Arunee Sriphanomwon, Boonchai Aree-uea, Khongdet Phasinam
    Multidisciplinary Science Journal, 2026
    The Lopsided Effects of Educational Trends on Quality Education for UN SDG Achievement: A Case Study of Neurodiverse and Marginalized Groups examined the uneven impact of educational trends on Quality Education for promoting the United Nations Sustainable Development Goals (SDGs) among neurodiverse students and marginalized communities. A study of 302 participants from a Nigerian community school revealed that educational trends have a moderate impact on promoting SDGs for both groups. For neurodiverse students, the trends posed health risks, such as fatigue from excessive screen time, while standardized testing methods were deemed unsuitable. Among marginalized groups, linguistic minorities faced barriers to accessing education. The research identified alternative educational approaches that can better promote SDGs, emphasizing teacher training programs for inclusive education and user-centered EdTech designs. The study found that educational trends have both benefits and drawbacks in supporting the promotion of SDGs, requiring accommodations to strike a balance. By acknowledging these challenges and implementing tailored solutions, educators and policymakers can create more inclusive learning environments that support the achievement of SDGs for all students, regardless of their abilities or backgrounds. This research highlights the need for a nuanced approach to educational trends, one that prioritizes equity and accessibility The results of the research showed that the lopsided effects of educational trends on promoting the United Nations SDGs in relation to neurodiverse students, overall, was at a moderate level. The lopsided effects of educational trends on promoting the United Nations SDGs in relation to marginalized and vulnerable groups, overall, was at a moderate level. Alternative educational approaches can better promote the SDGs and address the needs of neurodiverse learners and marginalized communities. Meanwhile, multiple linear regression analysis was employed to further strengthen the research’s tone.
  • Long-Term Electricity Demand Forecasting for Thailand’s Small Business Sector: An LSTM-Based Approach
    Puttiphong Jaroonsiriphan, Kayun Chantarasathaporn, Khongdet Phasinam
    International Journal of Emerging Research in Engineering Science and Management, 2026
    Accurate electricity demand forecasting is essential for Thailand’s energy system planning, particularly for the small business sector, whose consumption exhibits high variability (coefficient of variation: 26.34%). This study develops a Long Short-Term Memory (LSTM) model to forecast monthly electricity consumption of Thailand’s small business sector over a 12-month horizon from September 2025 to August 2026. The analysis is based on 284 months of historical consumption data (January 2002–August 2025) obtained from official national statistics. The forecasting framework employs Min–Max normalization and a supervised learning formulation with a 12-month lookback window. The dataset is chronologically divided into training (80%) and testing (20%) subsets, and model performance is evaluated using Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). The optimized LSTM model achieves strong forecasting accuracy, with a training RMSE of 93.93 and MAPE of 5.45%, and a testing RMSE of 143.68 and MAPE of 6.25%. These results meet the criterion for highly accurate forecasting (MAPE < 10%), demonstrating the model’s ability to capture long-term trends and seasonal patterns while generalizing well to unseen data. The findings highlight the suitability of LSTM-based models for long-term electricity demand forecasting in high-volatility small-business sectors and underscore their practical relevance for energy planning and policy development in Thailand.
  • Real-Time Monitoring and Positioning of Agricultural Tractors Using a Low-Cost GPS and IoT Device
    T. Phasinam, K. Phasinam, A. U-kaew, K. Piyathamrongchai, R. Hataitara, et al.
    International Journal of Geoinformatics, 2025
    This research aims to develop a low-cost GPS receiver device for positioning agricultural tractors, incorporating Differential GPS (DGPS) technology for enhanced accuracy using the Open-Source GIS Stack (OSGS). Integrated with Internet of Things (IoT) technology, the device was tested to receive GPS data and other relevant information, including geographic coordinates (latitude and longitude), tractor speed, tractor direction, date, time, and the number of satellites receiving signals. The DGPS setup involves using one receiver as a base station and another on the tractor, where the base station provides correction data to improve positioning accuracy. The data collected by the receiver is transmitted to a signal processing device for mapping the coordinates, creating a route of the tractor's movement that is displayed on a real-time Web Map Application. This process includes error correction to ensure high accuracy. The IoT device was installed on the left rear wheel of the agricultural tractor. Test results show that the data from the developed device has an accuracy of around 30-90 centimeters, which is acceptable and sufficient for agricultural tractor positioning applications. Furthermore, this system enables real-time monitoring of the tractor's operations.
  • Development and Economic Evaluation of a Banana Tree Shredder for Enhanced Pig Feed Production in Thailand
    Khongdet Phasinam, Thanwamas Phasinam, Sittichai Choosumrong, Tossaporn Incharoen, Dowroong Watcharinrat, Chatchawin Nualsri
    Aip Conference Proceedings, 2025
  • Efficiency of drip irrigation combined with Bacillus bacteria application in enhancing growth and yield of Jinda chilis
    Phraomas Charoenrak, Dowroong Watcharinrat, Suwonnakan Supamattra, Purin Akkarakultron, Thanwamas Phasinam, Khongdet Phasinam
    Multidisciplinary Science Journal, 2025
    The purpose of this study was to evaluate the efficiency of different drip irrigation schedules combined with the application of Bacillus bacteria (B. amyloliquefaciens BB165) on the growth and yield of Jinda chili plants. An experiment was conducted to compare four irrigation treatments: two sessions of 10 minutes each (control), three sessions of 5 minutes each, two sessions of 10 minutes combined with Bacillus bacteria, and three sessions of 5 minutes combined with Bacillus bacteria. Jinda chili seedlings were transplanted into plastic pots and treated accordingly. Plant heights were measured every 15 days, while yield weights were recorded every 30 days. Fresh plant and root weights were measured 90 days posttransplantation. The results indicated that three sessions of 5 minutes of drip irrigation significantly conserved water, reducing usage by up to 23.59% compared to the control, and increased plant heights by 6.81% to 14.00%. The combination of two sessions of 10 minutes of drip irrigation with Bacillus bacteria produced the highest fresh plant (199.75 g) and root weights (105.00 g). Yield weights showed no significant differences across treatments, though specific treatments exhibited higher yields at different intervals. Notably, three sessions of 5 minutes of drip irrigation with Bacillus bacteria resulted in the highest yield weight at 30 days (212.76 g), while two sessions of 10 minutes with Bacillus bacteria showed the best results at 90 days (184.09 g). In conclusion, optimizing drip irrigation schedules and integrating Bacillus bacteria can significantly enhance water efficiency and plant growth in chili cultivation. This study demonstrates that strategic irrigation practices combined with microbial interventions can lead to improved growth outcomes in chili plants.
  • Music attitudes and career aspirations: A study of master's degree students in private universities
    Dowroong Watcharinrat, Ek-karach Charoennit, Thanaphan Boonyarutkalin, Pattraporn Aupaiboon, Sujin Butdisuwan, Suwonnakan Supamattra, Nikorn Saengngam, Chudarat Watcharinrat, Khongdet Phasinam, Phanida Wamontree
    Multidisciplinary Science Journal, 2025
    This research aimed to explore the music attitudes and career choices of master’s degree students within the Faculty of Liberal Arts at private universities, with a focus on understanding the relationships among these variables. A total of 73 master’s degree students enrolled since 2021 were surveyed via questionnaires as research instruments. Statistical analyses, including frequency, percentage, mean, standard deviation (S.D.), and correlation coefficient (r), were performed to analyze the data. The findings revealed significant insights into students' attitudes toward music and their career preferences. With respect to music attitudes, the students demonstrated a profound belief in the societal importance of music and its role in enhancing the livability of society. Additionally, they expressed admiration for music professionals and recognized the significance of music-related professions such as musicians and music teachers. In terms of career choices, students prioritized working in organizations fostering inclusivity and embracing diversity among colleagues. They also emphasized the importance of studying subjects aligned with their strengths and aspirations and sought stability in leading companies or organizations. Surprisingly, the research concluded that there was no significant correlation between students' attitudes toward music and their career choices within this cohort. This study provides valuable insights for educators and career counselors, highlighting the nuanced dynamics between students' attitudes toward music and their career aspirations and indicating that these aspects may not necessarily be interlinked in this particular academic context.
  • AI-Based Aerial Camera Calibration and 3D Reconstruction Accuracy Evaluation
    Jittiphan Changkaew, Prasartporn Wongkamchang, Chamnan Pedchote, Khongdet Phasinam
    Advances in Artificial Intelligence and Machine Learning, 2025
    Accurate camera calibration is a cornerstone of aerial imaging, essential for precise 3D reconstruction, mapping, and motion estimation. Traditional calibration methods often depend on predefined objects and periodic recalibration, which are impractical in dynamic aerial environments. This study investigates the potential of AI-based calibration methods, specifically GeoCalib, CTRL-C, and DeepCalib, to address these challenges. Using the ISPRS Vaihingen dataset, evaluate these methods against the conventional approach. The research focuses on intrinsic parameter estimation and its impact on 3D reconstruction accuracy. Our findings reveal that CTRL-C achieved the highest precision, with a mean reconstruction error of 1.59e10−5 , significantly outperforming GeoCalib (1.0549) and DeepCalib (0.2110). Additionally, DeepCalib demonstrated strong performance in minimizing Chamfer Distance (0.4220) and Hausdorff Distance (0.2502), while GeoCalib exhibited broader error distributions. These results underscore the superior capability of AI-based techniques in delivering accurate and reliable calibration for aerial imaging systems.
  • The 21st century skills of the master's degree students in the school of liberal arts in private Universities
    Dowroong Watcharinrat, Sujin Butdisuwan, Thanaphan Boonyarutkalin, Khongdet Phasinam, Chudarat Watcharinrat, Nikorn Saengngarm, Suwonnakan Supamattra, Sutthiporn Boonsong
    Multidisciplinary Science Journal, 2024
    The objectives of this research are: 1) to study the skill levels and development needs of twenty-first century master's degree students, 2) to compare these skill levels and development needs by classifying students according to variables such as gender, age, work experience, and institution of graduation, and 3) to study the relationship between the level of skills and the need for developing twenty-first century skills of master's degree students. Questionnaires were distributed to master's degree students in the Faculty of Liberal Arts at a private university who studied from 2021 onward. A total of 80 questionnaires were distributed, and 73 responses were received. The statistical methods used in the research include frequency, percentage, mean and standard deviation, independent sample t-test, one-way ANOVA, and the correlation coefficient of variables (r). The research results found that: 1) the top three twenty-first century skills of students are media literacy, social skills, and information literacy. The top three needs for developing twenty-first century skills are cooperation, creative thinking, and communication skills. 2) The comparison of twenty-first century skills among students revealed no significant differences in skill levels based on gender and age. However, significant differences were found in skill levels based on the educational institutions and fields of study completed at the bachelor's degree level. No significant differences were found in the need for developing twenty-first century skills based on gender, age, educational institution, and field of study at the bachelor's degree level. 3) The level of twenty-first century skills is not related to the need for developing twenty-first century skills.
  • Optimizing Growth of Crystal Lettuce Using Controlled Environments in a Thai Plant Factory
    International Journal of Agriculture and Biosciences, 2024
    The agricultural sector in Thailand faces significant challenges due to high summer temperatures reaching 40-43C, which adversely affect plant growth and increase susceptibility to diseases.This study investigates the efficacy of using a Plant Factory with Artificial Lighting (PFAL) to optimize the growth conditions for Crystal Lettuce, aiming to enhance plant development and yield under controlled environments.The research focuses on determining the ideal environmental parameters within a PFAL to maximize the growth of Crystal Lettuce.Crystal Lettuce seeds were initially grown in cups filled with a perlitevermiculite mix (3:1) and a nutrient solution with an electrical conductivity (EC) of 1400-1600S/cm and pH of 5.5-6.2.These seedlings were exposed to white LED lights with an intensity of 17750Lux for 10 hours daily.After initial growth, the seedlings were transplanted into a nutrient solution with an EC of 1750-1830S/cm and subjected to yellow-white LED lights.The grow room, covering 160m 2 , maintained a controlled temperature of 30C, humidity at 71%, and CO2 levels between 876-942ppm.Light intensity across different planting layers ranged from 7474 to 25722Lux.Results demonstrated that Crystal Lettuce plants in the middle of the planting layer, receiving approximately 23691Lux, exhibited the most significant growth, with a plant height of 18.75cm, fresh weight of 91.50g, and canopy width of 22.00cm.In contrast, plants on the edges with lower light intensities showed reduced growth.The study concludes that controlled environmental conditions in a PFAL, particularly optimized light intensity, substantially improve the growth of Crystal Lettuce.This research supports the potential of PFAL systems to enhance agricultural productivity in regions with challenging climates.
  • Enhancing Banana Drying Efficiency: A Phase Change Heat Storage System Utilizing Charcoal Briquettes
    International Journal of Agriculture and Biosciences, 2024
    This study aimed to enhance the efficiency of banana drying processes through the development and testing of a phase change heat storage system utilizing heat from charcoal briquettes.The system was designed and modeled using SolidWorks software, incorporating a parabolic dome and a heat storage unit made of SS400 steel.Temperature measurements were conducted within the dome and the heat storage system and efficiency testing was performed by comparing drying methods.Moisture content testing of market-dried bananas provided baseline data, with an average moisture content of 26.51% (w.b.).Drying experiments using a parabolic dome solar dryer demonstrated a reduction in banana moisture content from 70.18 to 25.53% (w.b.) after 4 days.Subsequently, testing with the phase change heat storage system revealed a further reduction in moisture content to 25.58% (w.b.) within 3 days of drying.The systemmaintained temperatures inside the dome during nighttime, utilizing heat from charcoal briquettes to sustain drying processes.The results indicate that the phase change heat storage system significantly improves drying efficiency, with a 25% increase in production capacity compared to traditional solar drying methods.Implementation of this system offers a sustainable solution for banana processing, contributing to increased efficiency, reduced energy consumption, and enhanced product quality.This study underscores the potential of innovative drying technologies to address challenges in agricultural processing and promote sustainability within the industry.
  • Digital Education During Disruptive Times Like the COVID-19 Pandemic
    Samrat Ray, Khongdet Phasinam, Ghada Elkady
    Digitalization of Higher Education Opportunities and Threats, 2024
  • Optimizing confectionery production: A semi-automatic gummy jelly dropping machine design and performance evaluation
    Kanokwan Promjeen, Thanwamas Phasinam, Khongdet Phasinam
    Edelweiss Applied Science and Technology, 2024
  • Development and Optimization of a Tractor-Mounted Boring Mechanism for Efficient Fertilizer Application in Rubber Plantations
    Mongkol Kathapant, Yongyuth Sengdang, Khongdet Phasinam, Payungsak Junyusen
    Advances in Transdisciplinary Engineering, 2024
  • Comparative analysis of UAV detection and tracking performance Evaluating YOLOv5, YOLOv8, and YOLOv8 DeepSORT for enhancing anti-UAV systems
    Kamphon Suewongsuwan, Natchanun Angsuseranee, Prasatporn Wongkamchang, Khongdet Phasinam
    Edelweiss Applied Science and Technology, 2024
  • Design and efficiency testing of a prototype extruder for Bang Kaew dog food production
    Thanwamas Phasinam, Tossaporn Incharoen, Chatchawin Nualsri, Dowroong Watcharinrat, Khongdet Phasinam
    Journal of Asian Scientific Research, 2024
  • Strengths of computational systems of techniques using artificial intelligence in machine learning
    Shashikant V. Athawale, Indrajit Patra, Amol Dattatray Dhaygude, Vaibhav Rupapara, Thanwamas Kassanuk, Khongdet Phasinam
    International Journal of System of Systems Engineering, 2024
  • Application of Data Mining and Machine Learning in Food and Agriculture Industry towards Precision Agriculture
    Thanwamas Kassanuk, Khongdet Phasinam
    Aip Conference Proceedings, 2023
  • RETRACTED ARTICLE: Google’s new AI technology detects cardiac issues using retinal scan(Applied Nanoscience, (2023), 13, (3137))
    Surya Prasada Rao Borra, B. Sumathy, B. Mohammed Ismail, S. Naresh Kumar, Khongdet Phasinam, R. Ramesh
    Applied Nanoscience Switzerland, 2023
  • Development of IoT based smart monitor and control system using MQTT protocol and Node-RED for parabolic greenhouse solar drying
    Sittichai Choosumrong, Rhutairat Hataitara, Gitsada Panumonwatee, Venkatesh Raghavan, Chatchawin Nualsri, Thanwamas Phasinam, Khongdet Phasinam
    International Journal of Information Technology Singapore, 2023
  • An integrated approach for sustainable development of wastewater treatment and management system using IoT in smart cities
    Arodh Lal Karn, Sharnil Pandya, Abolfazl Mehbodniya, Farrukh Arslan, Dilip Kumar Sharma, Khongdet Phasinam, Muhammad Nauman Aftab, Regin Rajan, Ravi Kumar Bommisetti, Sudhakar Sengan
    Soft Computing, 2023
  • Reliability analysis of cement manufacturing technique in computerized clinker processing method
    Makendran C., Binaya Patnaik, Nilofer Hussaini, Jifara Chimdi Bikila, Ravindra Pathak, Khongdet Phasinam
    Aip Conference Proceedings, 2023
  • Utilization of fly ash for degradation based reliability
    Binaya Patnaik, Renu Mavi, Suraj Goswami, Pandurang Y. Patil, Khongdet Phasinam, M. Z. M. Nomani
    Aip Conference Proceedings, 2023
  • Reliability assessment of cement grinding device with nine components failed
    Prashant Kumar Gangwar, Jifara Chimdi Bikila, Ravindra Pathak, G. Arul Jothi, Anupam Singh, Khongdet Phasinam
    Aip Conference Proceedings, 2023
  • An Scientific Approach of Design and Development of a Garlic Peeling Machine
    International Journal of Intelligent Systems and Applications in Engineering, 2023
  • A Hybrid Binary Bird Swarm Optimization (BSO) and Dragonfly Algorithm (DA) for VM Allocation and Load Balancing in Cloud
    Thanwamas Kassanuk, Khongdet Phasinam
    International Journal of Cloud Applications and Computing, 2023
  • A Comparison of the Effects of Court-type Traditional Thai Massage and Prasaplai in Reducing Primary Dysmenorrhea
    Journal for Reattach Therapy and Developmental Diversities, 2023
  • Evaluating the Performance of Deep Learning Methods and Its Impact on Digital Marketing
    Ms. Gazala Masood, C. Indhumathi, Pacha. Malyadri, Krishna Mayi, B. K. Sumana, Khongdet Phasinam
    Smart Innovation Systems and Technologies, 2023
  • Data Detection in Wireless Sensor Network Based on Convex Hull and Naïve Bayes Algorithm
    Edwin Hernan Ramirez-Asis, Miguel Angel Silva Zapata, A. R. Sivakumaran, Khongdet Phasinam, Abhay Chaturvedi, R. Regin
    Eai Springer Innovations in Communication and Computing, 2023
  • Towards applicability of blockchain in agriculture sector
    Guna Sekhar Sajja, Kantilal Pitambar Rane, Khongdet Phasinam, Thanwamas Kassanuk, Ethelbert Okoronkwo, P. Prabhu
    Materials Today Proceedings, 2023
  • A Study on the Relationship Between Cloud Computing and Data Mining in Business Organizations
    Dilip Kumar Sharma, A. Dharmaraj, Alim Al Ayub Ahmed, K. Suresh Kumar, Khongdet Phasinam, Mohd Naved
    Smart Innovation Systems and Technologies, 2023
  • Classification and prediction of student performance data using various machine learning algorithms
    Harikumar Pallathadka, Alex Wenda, Edwin Ramirez-Asís, Maximiliano Asís-López, Judith Flores-Albornoz, Khongdet Phasinam
    Materials Today Proceedings, 2023
  • Evaluation of vulnerabilities in IoT-based intelligent agriculture systems
    Khongdet Phasinam, Thanwamas Kassanuk
    Autonomous Vehicles Smart Vehicles for Communication, 2022
  • Certain Investigation of Fake News Detection from Facebook and Twitter Using Artificial Intelligence Approach
    Roy Setiawan, Vidya Sagar Ponnam, Sudhakar Sengan, Mamoona Anam, Chidambaram Subbiah, Khongdet Phasinam, Manikandan Vairaven, Selvakumar Ponnusamy
    Wireless Personal Communications, 2022
  • Policy Formation of the Rajamangala University of Technology Thanyaburi for the Fiscal Year 2022
    Res Militaris, 2022
  • Analyzing the Impact of Lockdown in Controlling COVID-19 Spread and Future Prediction
    Mamoona Anam, Roy Setiawan, Sathiya Kumar Chinnappan, Nik Alif Amri Nik Hashim, Abolfazl Mehbodniya, Cherry Bhargava, Pardeep Kumar Sharma, Khongdet Phasinam, V. Subramaniyaswamy, Sudhakar Sengan
    International Journal of Uncertainty Fuzziness and Knowldege Based Systems, 2022
  • Design of blockchain based smart agriculture framework to ensure safety and security
    Thanwamas Kassanuk, Khongdet Phasinam
    Materials Today Proceedings, 2022
  • Supervised Machine Learning in Precision Agriculture
    International Journal of Mechanical Engineering, 2022
  • Impact of Internet of Things and Machine Learning in Smart Agriculture
    Thanwamas Kassanuk, Khongdet Phasinam
    Ecs Transactions, 2022
  • Machine Learning and Internet of Things (IoT) For Real-Time Image Classification in Smart Agriculture
    Khongdet Phasinam, Thanwamas Kassanuk
    Ecs Transactions, 2022
  • A comprehensive review on the implementation of technological Systems, Standards, and interfaces used in the food and agriculture industries
    Thanwamas Kassanuk, Khongdet Phasinam
    Materials Today Proceedings, 2022
  • Applicability of Internet of Things in Smart Farming
    Khongdet Phasinam, Thanwamas Kassanuk, Mohammad Shabaz
    Journal of Food Quality, 2022
  • Using Classification Data Mining for Predicting Student Performance
    Guna Sekhar Sajja, Harikumar Pallathadka, Khongdet Phasinam, Samrat Ray
    Ecs Transactions, 2022
  • Various Soft Computing Based Techniques for Developing Intrusion Detection Management System
    Guna Sekhar Sajjaa, Harikumar Pallathadka, Mohd Naved, Khongdet Phasinam
    Ecs Transactions, 2022
  • Internet of Things- Security Vulnerabilities and Countermeasures
    Abhishek Raghuvanshi, Umesh Kumar Singh, Thanwamas Kassanuk, Khongdet Phasinam
    Ecs Transactions, 2022
  • A Machine Learning Based Framework for Heart Disease Detection
    Harikumar Pallathadka, Mohd Naved, Khongdet Phasinam, Myla M. Arcinas
    Ecs Transactions, 2022
  • Machine Learning Techniques in Business Forecasting - A Performance Evaluation
    Guna Sekhar Sajja, Harikumar Pallathadka, Khongdet Phasinam, Myla M. Arcinas
    Ecs Transactions, 2022
  • Comparative Analysis of Environmental Internet of Things (IoT) and Its Techniques to Improve Profit Margin in a Small Business
    Khongdet Phasinam, Mohammed Usman, Sumona Bhattacharya, Thanwamas Kassanuk, Korakod Tongkachok
    Communications in Computer and Information Science, 2022
  • A System of Remote Patients' Monitoring and Alerting Using the Machine Learning Technique
    M. Dhinakaran, Khongdet Phasinam, Joel Alanya-Beltran, Kingshuk Srivastava, D. Vijendra Babu, Sitesh Kumar Singh
    Journal of Food Quality, 2022
  • Reliability Model for Joint Production and Preventive Maintenance System based on IoT
    R. Regin, Mamoona Anam, M. Kalyan Chakravarthi, Karthikeyan Kaliyaperumal, Khongdet Phasinam, K. Ashok
    Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy Icais 2022, 2022
  • Analyzing the Performance of Machine Learning Techniques in Disease Prediction
    Khongdet Phasinam, Tamal Mondal, Dony Novaliendry, Cheng-Hong Yang, Chiranjit Dutta, Mohammad Shabaz
    Journal of Food Quality, 2022
  • A review on role of artificial intelligence in food processing and manufacturing industry
    Edwin Ramirez-Asis, Juan Vilchez-Carcamo, Chetan M. Thakar, Khongdet Phasinam, Thanwamas Kassanuk, Mohd Naved
    Materials Today Proceedings, 2022
  • Towards applicability of machine learning techniques in agriculture and energy sector
    K. Arumugam, Yarnagula Swathi, Domenic T. Sanchez, Malik Mustafa, Chirasak Phoemchalard, Khongdet Phasinam, Ethelbert Okoronkwo
    Materials Today Proceedings, 2022
  • An investigation of various applications and related challenges in cloud computing
    Harikumar Pallathadka, Guna Sekhar Sajja, Khongdet Phasinam, Mahyudin Ritonga, Mohd Naved, Rajni Bansal, Jose Quiñonez-Choquecota
    Materials Today Proceedings, 2022
  • Application of machine learning techniques in rice leaf disease detection
    Harikumar Pallathadka, Pavankumar Ravipati, Guna Sekhar Sajja, Khongdet Phasinam, Thanwamas Kassanuk, Domenic T. Sanchez, P. Prabhu
    Materials Today Proceedings, 2022
  • Application of IoT and Cloud Computing in Automation of Agriculture Irrigation
    Khongdet Phasinam, Thanwamas Kassanuk, Priyanka P. Shinde, Chetan M. Thakar, Dilip Kumar Sharma, Md. Khaja Mohiddin, Abdul Wahab Rahmani
    Journal of Food Quality, 2022
  • Intrusion Detection Using Machine Learning for Risk Mitigation in IoT-Enabled Smart Irrigation in Smart Farming
    Abhishek Raghuvanshi, Umesh Kumar Singh, Guna Sekhar Sajja, Harikumar Pallathadka, Evans Asenso, Mustafa Kamal, Abha Singh, Khongdet Phasinam
    Journal of Food Quality, 2022
  • RETRACTED: Towards Development of Machine Learning Framework for Enhancing Security in Internet of Things
    Mutyalaiah Paricherla, Sallagundla Babu, Khongdet Phasinam, Harikumar Pallathadka, Abu Sarwar Zamani, Vipul Narayan, Surendra Kumar Shukla, Hussien Sobahi Mohammed
    Security and Communication Networks, 2022
  • Analysis of an Arduino based solar tracking system
    A Mohamad, MTA Rahman, K Phasinam, MS Bin Mohamad, MAM Saad, SY Chionh
    Journal of Physics Conference Series, 2021
  • Designing and Constructing a Cassava Slicing Machine for Household Use
    International Journal of Mechanical Engineering, 2021
  • An Investigation on Crop Yield Prediction Using Machine Learning
    Guna Sekhar Sajja, Subhesh Saurabh Jha, Hicham Mhamdi, Mohd Naved, Samrat Ray, Khongdet Phasinam
    Proceedings of the 3rd International Conference on Inventive Research in Computing Applications Icirca 2021, 2021
  • Towards Application of Machine Learning in Classification and Prediction of Heart Disease
    Guna Sekhar Sajja, Malik Mustafa, Khongdet Phasinam, Karthikeyan Kaliyaperumal, Randy Joy Magno Ventayen, Thanwamas Kassanuk
    Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems Icesc 2021, 2021
  • A Framework for Secure Healthcare System Using Blockchain and Smart Contracts
    Santosh T. Jagtap, Chetan M. Thakar, Ouail El imrani, Khongdet Phasinam, Shaifali Garg, Randy Joy Magno Ventayen
    Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems Icesc 2021, 2021
  • X ray diffraction (XRD) analysis and evaluation of antioxidant activity of copper oxide nanoparticles synthesized from leaf extract of Cissus vitiginea
    Minakshi A. Thakar, Subhesh Saurabh Jha, Khongdet Phasinam, Ravi Manne, Yaser Qureshi, V.V. Hari Babu
    Materials Today Proceedings, 2021
  • 3d Printing: Basic principles and applications
    Chetan M. Thakar, Shailesh S. Parkhe, Ankit Jain, Khongdet Phasinam, G. Murugesan, Randy Joy Magno Ventayen
    Materials Today Proceedings, 2021
  • Rainfall Prediction Using Deep Mining Strategy for Detection
    Karthikeyan Kaliyaperumal, Afikah Rahim, D. K. Sharma, R. Regin, Swati Vashisht, Khongdet Phasinam
    Proceedings 2nd International Conference on Smart Electronics and Communication Icosec 2021, 2021
  • Towards application of various machine learning techniques in agriculture
    Santosh T. Jagtap, Khongdet Phasinam, Thanwamas Kassanuk, Subhesh Saurabh Jha, Tanmay Ghosh, Chetan M. Thakar
    Materials Today Proceedings, 2021
  • Technical Support for Detection and Prediction of Rainfall
    D. Hemavathi, V. Ramesh Kumar, R. Regin, S. Suman Rajest, Khongdet Phasinam, Saurabh Singh
    Proceedings 2nd International Conference on Smart Electronics and Communication Icosec 2021, 2021
  • Effect of succinic acid on compression strength concrete material
    Keshav Parashar, Dr. Rakesh kumar Dubey, M. Padmaja, Khongdet Phasinam, Dr. J. Tracy Tina Angelina, Piyush Gupta
    Materials Today Proceedings, 2021