Abir hossen

University of South Carolina, Computer Science and Engineering, Graduate Student

University of Southern California, Computer Science, Graduate Student

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I am a Ph.D. student in the Computer Science and Engineering department at University of South Carolina. I am currently working at AISys Lab as a graduate research assistant and conducting research on developing a Space Lander for the NASA Europa mission in collaboration with the NASA Ocean Worlds autonomy testbed team, JPL, and Carnegie Mellon University.

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Total nitrogen estimation in agricultural soils via aerial multispectral imaging and LIBS

Scientific Reports, 2021

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6 Wheeled Mars rover design for terrain traversing, equipment servicing, astronaut assistance and on-board testing

IEEE/SICE International Symposium on System Integration, 2016

Since the success of the Mars Pathfinder, a new chapter of space exploration began focusing on re... more Since the success of the Mars Pathfinder, a new chapter of space exploration began focusing on reducing the complexity of the rover and making it more autonomous, multifunctional, lightweight even at extreme adversities. A student based design for a competition allowed the researchers in this paper to explore a design that would meet those requirements. This paper presents the design of a six wheeled, triangular shaped chassis, having multi suspension based rover. This rover is integrated with a 2.4GHz communication system that not only allows the rover to be operated from a distance of 1km, but also allows the researchers to collect soil samples and test them on board the rover using a Microlab box. The rover also shows superior maneuverability by being able to turn 360° on the spot and able to scale obstacles of almost 1 feet. The performance of the design was also tested at a global competition — University Rover Challenge 2016 organized by The Mars Society held at Utah, USA, where this design came in 8th for the Phobos category. This competition only invited 30 rovers out of the 63 that applied from 12 different countries.

DeepQGHO: Quantized Greedy Hyperparameter Optimization in Deep Neural Networks for on-the-fly Learning

IEEE Access

Hyperparameter optimization or tuning plays a significant role in the performance and reliability... more Hyperparameter optimization or tuning plays a significant role in the performance and reliability of deep learning (DL). Many hyperparameter optimization algorithms have been developed for obtaining better validation accuracy in DL training. Most state-of-the-art hyperparameters are computationally expensive due to a focus on validation accuracy. Therefore, they are unsuitable for online or on-thefly training applications which require computational efficiency. In this paper, we develop a novel greedy approach-based hyperparameter optimization (GHO) algorithm for faster training applications, e.g., on-thefly training. We perform an empirical study to compute the performance such as computation time and energy consumption of the GHO and compare it with two state-of-the-art hyperparameter optimization algorithms. We also deploy the GHO algorithm in an edge device to validate the performance of our algorithm. We perform post-training quantization to the GHO algorithm to reduce inference time and latency.

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Hybrid Ant Swarm-Based Data Clustering

2021 IEEE World AI IoT Congress (AIIoT)

Developing a Mobile Automated Medical Assistant for Hospitals in Bangladesh

by Abir hossen and Md Ali Azam

2021 IEEE World AI IoT Congress (AIIoT), 2021

This paper introduces a mobile robot that is designed to assist medical professionals in hospital... more This paper introduces a mobile robot that is designed to assist medical professionals in hospitals with daily simple tasks which allow the staff in turn to optimize their resources. A prototype of this robot was deployed at the Bangabandhu Sheikh Mujib Medical University in Bangladesh with funding from the Government of Bangladesh, USAID and UNDP. This robot performed its functions as an Automated Medical Assistant (AMA) by delivering to and interacting with patients and medical staff during its trial phase in 2018. This paper presents the robot to have an intuitive user interface, a userfriendly mode of communication, smart features in its commandand-control system, security, and energy optimization. The smart robot is able to navigate its way to specific patients as well as avoid obstacles and finally navigate back to its charging station once its energy is depleted.

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Total nitrogen estimation in agricultural soils via aerial multispectral imaging and LIBS

Measuring soil health indicators (SHIs), particularly soil total nitrogen (TN), is an important a... more Measuring soil health indicators (SHIs), particularly soil total nitrogen (TN), is an important and challenging task that affects farmers' decisions on timing, placement, and quantity of fertilizers applied in the farms. Most existing methods to measure SHIs are in-lab wet chemistry or spectroscopybased methods, which require significant human input and effort, time-consuming, costly, and are low-throughput in nature. To address this challenge, we develop an artificial intelligence (AI)-driven near real-time unmanned aerial vehicle (UAV)-based multispectral sensing solution (UMS) to estimate soil TN in an agricultural farm. TN is an important macro-nutrient or SHI that directly affects the crop health. Accurate prediction of soil TN can significantly increase crop yield through informed decision making on the timing of seed planting, and fertilizer quantity and timing. The ground-truth data required to train the AI approaches is generated via laser-induced breakdown spectroscopy (LIBS), which can be readily used to characterize soil samples, providing rapid chemical analysis of the samples and their constituents (e.g., nitrogen, potassium, phosphorus, calcium). Although LIBS was previously applied for soil nutrient detection, there is no existing study on the integration of LIBS with UAV multispectral imaging and AI. We train two machine learning (ML) models including multilayer perceptron regression and support vector regression to predict the soil nitrogen using a suite of data classes including multispectral characteristics of the soil and crops in red (R), near-infrared, and green (G) spectral bands, computed vegetation indices (NDVI), and environmental variables including air temperature and relative humidity (RH). To generate the ground-truth data or the training data for the machine learning models, we determine the N spectrum of the soil samples (collected from a farm) using LIBS and develop a calibration model using the correlation between actual TN of the soil samples and the maximum intensity of N spectrum. In addition, we extract the features from the multispectral images captured while the UAV follows an autonomous flight plan, at different growth stages of the crops. The ML model's performance is tested on a fixed configuration space for the hyperparameters using various hyper-parameter optimization techniques at three different wavelengths of the N spectrum. Soil health indicators are a composite set of measurable physical, chemical and biological properties which can be used to determine soil health status. Among the chemical indicators, we particularly focus on nitrogen (N) because N is the most limiting nutrient in many of the world's agricultural areas 1. Insufficient use of N causes economic loss, in contrast, excessive use of N implies wasting fertilizer, causes nitrate pollution, and increases the cost 2,3. Nitrogen treatment can account for up to 30% of the total production cost 4. Chlorophyll meter (CM) measures the chlorophyll content of crops to estimate their N nutrition status. In recent years, the use of CM has increased among researchers and farmers 5,6. For instance, N application rates for corn were determined using the adjusted R 2 of the relationship between nitrogen rate difference (ND) and CM readings 7. However, CM-based methods fail to capture the spatial variability that is often present within the field. For N management, determination of spatial patterns is necessary but requires collection and analysis of a large number of samples which is labor-intensive and time-consuming 2,6. Satellite-based remote sensing is one alternative to ground-based measurements. Satellite-based techniques utilize images at the spectral level for crop growth monitoring and real-time management 8-10. For instance, vegetation indices (VIs), evaluated using the data obtained from satellite-based multispectral sensors, have been used to detect the N stress at V4-V7 (4-7 leaves with visible leaf collar) stages 11-13. However, satellite-based sensing

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6 Wheeled Mars Rover Design for Terrain Traversing, Equipment Servicing, Astronaut Assistance and On-board Testing

by Abir hossen, Md Mahfuzur Rahman, and Farhan Mamun

Since the success of the Mars Pathfinder, a new chapter of space exploration began focusing on re... more Since the success of the Mars Pathfinder, a new chapter of space exploration began focusing on reducing the complexity of the rover and making it more autonomous, multifunctional, lightweight even at extreme adversities. A student based design for a competition allowed the researchers in this paper to explore a design that would meet those requirements. This paper presents the design of a six wheeled, triangular shaped chassis, having multi suspension based rover. This rover is integrated with a 2.4GHz communication system that not only allows the rover to be operated from a distance of 1km, but also allows the researchers to collect soil samples and test them on board the rover using a Microlab box. The rover also shows superior maneuverability by being able to turn 360° on the spot and able to scale obstacles of almost 1 feet. The performance of the design was also tested at a global competition – University Rover Challenge 2016 organized by The Mars Society held at Utah, USA, where this design came in 8th for the Phobos category. This competition only invited 30 rovers out of the 63 that applied from 12 different countries.

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Implementation and Performance Comparison for two versions of Eye Tracking based Robotic Arm Movement

by Abir hossen and Yousuf Amin

This paper is presenting the findings of a student project that involved using an emerging techno... more This paper is presenting the findings of a student project that involved using an emerging technology of eye tracking to help handicapped people with mobility options. The designers' intention was to implement a prototype and test its feasibility for helping the poor and physically challenged people in Bangladesh. The working prototype has been designed with two versions. The first one is able to interface the video based eye tracking technology with a laptop so that the bedridden patient is able to control electrical appliances such as a robotic arm. The second version is tested for controlling the same robotic arm but with a standalone head unit with the intention to give the user a greater degree of freedom in mobility. Both versions are developed with the intention to help people with disabilities and improve their quality of life.

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Total nitrogen estimation in agricultural soils via aerial multispectral imaging and LIBS

Scientific Reports, 2021

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6 Wheeled Mars rover design for terrain traversing, equipment servicing, astronaut assistance and on-board testing

IEEE/SICE International Symposium on System Integration, 2016

DeepQGHO: Quantized Greedy Hyperparameter Optimization in Deep Neural Networks for on-the-fly Learning

IEEE Access

Download

Hybrid Ant Swarm-Based Data Clustering

2021 IEEE World AI IoT Congress (AIIoT)

Developing a Mobile Automated Medical Assistant for Hospitals in Bangladesh

by Abir hossen and Md Ali Azam

2021 IEEE World AI IoT Congress (AIIoT), 2021

Download

Total nitrogen estimation in agricultural soils via aerial multispectral imaging and LIBS

Download

6 Wheeled Mars Rover Design for Terrain Traversing, Equipment Servicing, Astronaut Assistance and On-board Testing

by Abir hossen, Md Mahfuzur Rahman, and Farhan Mamun

Since the success of the Mars Pathfinder, a new chapter of space exploration began focusing on re... more Since the success of the Mars Pathfinder, a new chapter of space exploration began focusing on reducing the complexity of the rover and making it more autonomous, multifunctional, lightweight even at extreme adversities. A student based design for a competition allowed the researchers in this paper to explore a design that would meet those requirements. This paper presents the design of a six wheeled, triangular shaped chassis, having multi suspension based rover. This rover is integrated with a 2.4GHz communication system that not only allows the rover to be operated from a distance of 1km, but also allows the researchers to collect soil samples and test them on board the rover using a Microlab box. The rover also shows superior maneuverability by being able to turn 360° on the spot and able to scale obstacles of almost 1 feet. The performance of the design was also tested at a global competition – University Rover Challenge 2016 organized by The Mars Society held at Utah, USA, where this design came in 8th for the Phobos category. This competition only invited 30 rovers out of the 63 that applied from 12 different countries.

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Implementation and Performance Comparison for two versions of Eye Tracking based Robotic Arm Movement

by Abir hossen and Yousuf Amin

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