Projects per year
Personal profile
Biography
Mohammed Ayoub Juman is a Lecturer in the Mechatronics Discipline under the School of Engineering at Monash University Malaysia. His research interests are focused on Agricultural Robotics, Automation, Machine Vision, Machine Learning and Neural Networks, with the main focus being on introducing automation into agricultural areas. His past research focused on the creation of a navigation system for an autonomous mobile robot designed to function in Oil Palm Plantations.
His research goal is to help improve the standard of living of people via smart systems as well as to help industries that could use automation to combat a lack of labour force. This could also impact agricultural areas where new research on machines, sensors or data processing techniques can result in better growth of crops, higher yields and better management of plantation areas.
Research interests
My research is motivated by a desire to contribute to the betterment of human life by the introduction of automation where applicable. My goal is to help those areas that could be improved by automation that currently suffers from a lack of manpower or resources. The main aim is to help those individuals or industries increase their productivity while using their current workforce, instead of replacing them. My research methodology involves the use of machine vision and learning techniques, as well as mobile robots and sensors in applicable areas, either indoors or outdoors, especially in an agricultural domain. My current primary focus is on the application of automation to oil palm plantations, as a continuation of the work done during my doctorate.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Research area keywords
- Autonomous Robots
- Artificial Intelligence
- Machine Vision
- Industrial Automation
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Agriculture 4.0 - Investigation on Fusing Digital Twins and Deep Learning for improving Agricultural Yield and Autonomy
Juman, M. A., Ragavan, V., Ta Yeong, W., Lim, J., Hazliza, N. & Gobithaasan, R. U.
1/10/23 → 30/09/25
Project: Research
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A Novel Incremental Learning with PCA Convolutional Neural Network (ILPCNN) for Fine-Grained Vehicle Model Recognition
Chee Pin, T. (Primary Chief Investigator (PCI)), Hui Ying, K. (Chief Investigator (CI)), Foo Chong, S. (Chief Investigator (CI)), Juman, M. A. (Chief Investigator (CI)) & Lim, C. P. (Chief Investigator (CI))
7/09/21 → 6/03/25
Project: Research
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Attention Mechanisms in Deep Learning Models for Short-Term Energy Load Forecasting
Sendanayake, C. M., Juman, M. A., Tan, W.-S. & Tan, C. P., 2023, 2023 IEEE 21st Student Conference on Research and Development, SCOReD 2023. IEEE, Institute of Electrical and Electronics Engineers, p. 87-92 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other
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Integrated flood vulnerability assessment for vulnerable communities in Malaysia
Zahidi, I., Sumali, A., Lee, L. F., Ying, E. L. J., Krishnan, L., Sue, C. Y. & Juman, M. A., 24 Apr 2023, SSRN, p. 1-20, 20 p.Research output: Working paper › Working Paper › Research
Open AccessFile -
Shape-invariant indirect hardness estimation for a soft vacuum-actuated gripper with an onboard depth camera
Ling, T. R., Juman, M. A., Nurzaman, S. G. & Tan, C. P., 2023, 2023 IEEE International Conference on Soft Robotics, RoboSoft 2023. IEEE, Institute of Electrical and Electronics EngineersResearch output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other
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A novel electrical impedance function to estimate central aortic blood pressure waveforms
Sooriamoorthy, D., Shanmugam, S. A. & Juman, M. A., Jul 2021, In: Biomedical Signal Processing and Control. 68, 10 p., 102649.Research output: Contribution to journal › Article › Research › peer-review
68 Citations (Scopus) -
A regression unsupervised incremental learning algorithm for solar irradiance prediction
Puah, B. K., Chong, L. W., Wong, Y. W., Begam, K. M., Khan, N., Juman, M. A. & Rajkumar, R. K., Feb 2021, In: Renewable Energy. 164, p. 908-925 18 p.Research output: Contribution to journal › Article › Research › peer-review
52 Citations (Scopus)