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Smart farming has become imperative these days due to competition, and use of Unmanned Aerial Vehicle (UAV) imagery is becoming an integral part of the process. Machine learning techniques have been successfully applied to capture UAV imagery of various spectral bands to identify weed infestations. Identification of weeds in chilli crop is a challenging task. In this paper, RGB images captured by drones have been used to detect weed in chilli field. This task has been addressed through orthomasaicking of images, feature extraction, labelling of images to train machine learning algorithms, and use of unsupervised learning with random forest for classification. MATLAB has been used for all computations and out-of-bag accuracy achieved for identifying weeds is 96\(\%\).
Nahina Islam; Mamunur Rashid; Santoso Wibowo; Saleh Wasimi; Ahsan Morshed; Chengyuan Xu; Steven Moore. Machine Learning Based Approach for Weed Detection in Chilli Field Using RGB Images. Advances in Intelligent Systems and Computing 2021, 1097 -1105.
AMA StyleNahina Islam, Mamunur Rashid, Santoso Wibowo, Saleh Wasimi, Ahsan Morshed, Chengyuan Xu, Steven Moore. Machine Learning Based Approach for Weed Detection in Chilli Field Using RGB Images. Advances in Intelligent Systems and Computing. 2021; ():1097-1105.
Chicago/Turabian StyleNahina Islam; Mamunur Rashid; Santoso Wibowo; Saleh Wasimi; Ahsan Morshed; Chengyuan Xu; Steven Moore. 2021. "Machine Learning Based Approach for Weed Detection in Chilli Field Using RGB Images." Advances in Intelligent Systems and Computing , no. : 1097-1105.
This paper explores the potential of machine learning algorithms for weed and crop classification from UAV images. The identification of weeds in crops is a challenging task that has been addressed through orthomosaicing of images, feature extraction and labelling of images to train machine learning algorithms. In this paper, the performances of several machine learning algorithms, random forest (RF), support vector machine (SVM) and k-nearest neighbours (KNN), are analysed to detect weeds using UAV images collected from a chilli crop field located in Australia. The evaluation metrics used in the comparison of performance were accuracy, precision, recall, false positive rate and kappa coefficient. MATLAB is used for simulating the machine learning algorithms; and the achieved weed detection accuracies are 96% using RF,
Nahina Islam; Mamunur Rashid; Santoso Wibowo; Cheng-Yuan Xu; Ahsan Morshed; Saleh Wasimi; Steven Moore; Sk Rahman. Early Weed Detection Using Image Processing and Machine Learning Techniques in an Australian Chilli Farm. Agriculture 2021, 11, 387 .
AMA StyleNahina Islam, Mamunur Rashid, Santoso Wibowo, Cheng-Yuan Xu, Ahsan Morshed, Saleh Wasimi, Steven Moore, Sk Rahman. Early Weed Detection Using Image Processing and Machine Learning Techniques in an Australian Chilli Farm. Agriculture. 2021; 11 (5):387.
Chicago/Turabian StyleNahina Islam; Mamunur Rashid; Santoso Wibowo; Cheng-Yuan Xu; Ahsan Morshed; Saleh Wasimi; Steven Moore; Sk Rahman. 2021. "Early Weed Detection Using Image Processing and Machine Learning Techniques in an Australian Chilli Farm." Agriculture 11, no. 5: 387.
Smart farming has the potential to overcome the challenge of 2050 to feed 10 billion people. Both artificial intelligence (AI) and the internet of things (IoT) have become critical prerequisites to smart farming due to their high interoperability, sensors, and cutting-edge technologies. Extending the role of responsible leadership, this paper proposes an AI and IoT based smart farming system in Bangladesh. With a comprehensive literature review, this paper counsels the need to go beyond the simple application of traditional farming and irrigation practices and recommends implementing smart farming enabling responsible leadership to uphold sustainable agriculture. It contributes to the current literature of smart farming in several ways. First, this paper helps to understand the prospect and challenges of both AI and IoT and the requirement of smart farming in a nonwestern context. Second, it clarifies the interventions of responsible leadership into Bangladesh’s agriculture sector and justifies the demand for sustainable smart farming. Third, this paper is a step forward to explore future empirical studies for the effective and efficient use of AI and IoT to adopt smart farming. Finally, this paper will help policymakers to take responsible initiatives to plan and apply smart farming in a developing economy like Bangladesh.
Amlan Haque; Nahina Islam; Nahidul Samrat; Shuvashis Dey; Biplob Ray. Smart Farming through Responsible Leadership in Bangladesh: Possibilities, Opportunities, and Beyond. Sustainability 2021, 13, 4511 .
AMA StyleAmlan Haque, Nahina Islam, Nahidul Samrat, Shuvashis Dey, Biplob Ray. Smart Farming through Responsible Leadership in Bangladesh: Possibilities, Opportunities, and Beyond. Sustainability. 2021; 13 (8):4511.
Chicago/Turabian StyleAmlan Haque; Nahina Islam; Nahidul Samrat; Shuvashis Dey; Biplob Ray. 2021. "Smart Farming through Responsible Leadership in Bangladesh: Possibilities, Opportunities, and Beyond." Sustainability 13, no. 8: 4511.
IEC 61850 is one of the most prominent communication standards adopted by the smart grid community due to its high scalability, multi-vendor interoperability, and support for several input/output devices. Generic Object-Oriented Substation Events (GOOSE), which is a widely used communication protocol defined in IEC 61850, provides reliable and fast transmission of events for the electrical substation system. This paper investigates the security vulnerabilities of this protocol and analyzes the potential impact on the smart grid by rigorously analyzing the security of the GOOSE protocol using an automated process and identifying vulnerabilities in the context of smart grid communication. The vulnerabilities are tested using a real-time simulation and industry standard hardware-in-the-loop emulation. An in-depth experimental analysis is performed to demonstrate and verify the security weakness of the GOOSE publish-subscribe protocol towards the substation protection within the smart grid setup. It is observed that an adversary who might have familiarity with the substation network architecture can create falsified attack scenarios that can affect the physical operation of the power system. Extensive experiments using the real-time testbed validate the theoretical analysis, and the obtained experimental results prove that the GOOSE-based IEC 61850 compliant substation system is vulnerable to attacks from malicious intruders.
Haftu Reda; Biplob Ray; Pejman Peidaee; Adnan Anwar; Abdun Mahmood; Akhtar Kalam; Nahina Islam. Vulnerability and Impact Analysis of the IEC 61850 GOOSE Protocol in the Smart Grid. Sensors 2021, 21, 1554 .
AMA StyleHaftu Reda, Biplob Ray, Pejman Peidaee, Adnan Anwar, Abdun Mahmood, Akhtar Kalam, Nahina Islam. Vulnerability and Impact Analysis of the IEC 61850 GOOSE Protocol in the Smart Grid. Sensors. 2021; 21 (4):1554.
Chicago/Turabian StyleHaftu Reda; Biplob Ray; Pejman Peidaee; Adnan Anwar; Abdun Mahmood; Akhtar Kalam; Nahina Islam. 2021. "Vulnerability and Impact Analysis of the IEC 61850 GOOSE Protocol in the Smart Grid." Sensors 21, no. 4: 1554.
To reach the goal of sustainable agriculture, smart farming is taking advantage of the Unmanned Aerial Vehicles (UAVs) and Internet of Things (IoT) paradigm. These smart farms are designed to be run by interconnected devices and vehicles. Some enormous potentials can be achieved by the integration of different IoT technologies to achieve automated operations with minimum supervision. This paper outlines some major applications of IoT and UAV in smart farming, explores the communication technologies, network functionalities and connectivity requirements for Smart farming. The connectivity limitations of smart agriculture and it’s solutions are analysed with two case studies. In case study-1, we propose and evaluate meshed Long Range Wide Area Network (LoRaWAN) gateways to address connectivity limitations of Smart Farming. While in case study-2, we explore satellite communication systems to provide connectivity to smart farms in remote areas of Australia. Finally, we conclude the paper by identifying future research challenges on this topic and outlining directions to address those challenges.
Nahina Islam; Mamunur Rashid; Faezeh Pasandideh; Biplob Ray; Steven Moore; Rajan Kadel. A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming. Sustainability 2021, 13, 1821 .
AMA StyleNahina Islam, Mamunur Rashid, Faezeh Pasandideh, Biplob Ray, Steven Moore, Rajan Kadel. A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming. Sustainability. 2021; 13 (4):1821.
Chicago/Turabian StyleNahina Islam; Mamunur Rashid; Faezeh Pasandideh; Biplob Ray; Steven Moore; Rajan Kadel. 2021. "A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming." Sustainability 13, no. 4: 1821.
Agriculture is an important source of greenhouse gas emissions. It is one of the economic sectors that impacts both directly and indirectly towards climate change which contributes to greenhouse gas emissions. There has been a continuous trend of agricultural greenhouse gas emissions reduction technologies, but any step taken in this direction must not negatively affect farm productivity and economics. For the agriculture sector to achieve reduced GHG emission, climate-smart activities and improved food security will be needed for this sector to become a climate-smart landscape. Climate-smart technologies are effective at targeting inputs to the fields, helping to lower greenhouse gas emissions. This article explores the key sources of carbon emissions within the agriculture sector and reviews efficient ways to GHG emission via Smart Farming technology. Based on the public archive GHG datasets, we have found that livestock farming is the largest GHG emission sector among other agricultural sectors and responsible for 70% of the total emission. Besides, we also show that Queensland is the largest agricultural GHG contributor compared to other states and territories. The article also captures any possible sources within smart farming that may contribute to carbon emissions and suggest ways to reduce GHG emissions. Besides, an Australian-based best management practice approach is discussed to review the emissions reduction strategy based on climate-specific technology to help the farmers and other stakeholders take environmentally-friendly agricultural decisions.
Heena Panchasara; Nahidul Samrat; Nahina Islam. Greenhouse Gas Emissions Trends and Mitigation Measures in Australian Agriculture Sector—A Review. Agriculture 2021, 11, 85 .
AMA StyleHeena Panchasara, Nahidul Samrat, Nahina Islam. Greenhouse Gas Emissions Trends and Mitigation Measures in Australian Agriculture Sector—A Review. Agriculture. 2021; 11 (2):85.
Chicago/Turabian StyleHeena Panchasara; Nahidul Samrat; Nahina Islam. 2021. "Greenhouse Gas Emissions Trends and Mitigation Measures in Australian Agriculture Sector—A Review." Agriculture 11, no. 2: 85.
Multi-tier heterogeneous Networks (HetNets) with dense deployment of small cells in 5G networks are expected to effectively meet the ever increasing data traffic demands and offer improved coverage in indoor environments. However, HetNets are raising major concerns to mobile network operators such as complex distributed control plane management, handover management issue, increases latency and increased energy expenditures. Sleep mode implementation in multi-tier 5G networks has proven to be a very good approach for reducing energy expenditures. In this paper, a Markov Decision Process (MDP)-based algorithm is proposed to switch between three different power consumption modes of a base station (BS) for improving the energy efficiency and reducing latency in 5G networks. The MDP-based approach intelligently switches between the states of the BS based on the offered traffic while maintaining a prescribed minimum channel rate per user. Simulation results show that the proposed MDP algorithm together with the three-state BSs results in a significant gain in terms of energy efficiency and latency.
Nahina Islam; Ammar Alazab; Johnson Agbinya. Energy Efficient and Delay Aware 5G Multi-Tier Network. Remote Sensing 2019, 11, 1019 .
AMA StyleNahina Islam, Ammar Alazab, Johnson Agbinya. Energy Efficient and Delay Aware 5G Multi-Tier Network. Remote Sensing. 2019; 11 (9):1019.
Chicago/Turabian StyleNahina Islam; Ammar Alazab; Johnson Agbinya. 2019. "Energy Efficient and Delay Aware 5G Multi-Tier Network." Remote Sensing 11, no. 9: 1019.
This paper offers a review of different types of Error Correction Scheme (ECS) used in communication systems in general, which is followed by a summary of the IEEE standard for Wireless Body Area Network (WBAN). The possible types of channels and network models for WBAN are presented that are crucial to the design and implementation of ECS. Following that, a literature review on the proposed ECSs for WBAN is conducted based on different aspects. One aspect of the review is to examine what type of parameters are considered during the research work. The second aspect of the review is to analyse how the reliability is measured and whether the research works consider the different types of reliability and delay requirement for different data types or not. The review indicates that the current literatures do not utilize the constraints that are faced by WBAN nodes during ECS design. Subsequently, we put forward future research challenges and opportunities on ECS design and the implementation for WBAN when considering computational complexity and the energy-constrained nature of nodes.
Rajan Kadel; Nahina Islam; Khandakar Ahmed; Sharly J. Halder. Opportunities and Challenges for Error Correction Scheme for Wireless Body Area Network—A Survey. Journal of Sensor and Actuator Networks 2018, 8, 1 .
AMA StyleRajan Kadel, Nahina Islam, Khandakar Ahmed, Sharly J. Halder. Opportunities and Challenges for Error Correction Scheme for Wireless Body Area Network—A Survey. Journal of Sensor and Actuator Networks. 2018; 8 (1):1.
Chicago/Turabian StyleRajan Kadel; Nahina Islam; Khandakar Ahmed; Sharly J. Halder. 2018. "Opportunities and Challenges for Error Correction Scheme for Wireless Body Area Network—A Survey." Journal of Sensor and Actuator Networks 8, no. 1: 1.
In recent times, aerial base stations(AeBSs) are being investigated to provide wireless coverage to terrestrial radio terminals. The advantages of using aerial platforms to provide wireless coverage are many including larger coverage in remote areas, better line-of-sight conditions etc. Energy is a scarce resource for aerial base stations, hence the wise management of energy is quite beneficial for the aerial network. In this context, we study the means of reducing the total energy consumption by designing and implementing an energy efficient aerial base station as presented in this paper. Sleep mode implementation in base stations (BSs) has proven to be a very good approach for improving the energy efficiency and in this paper we propose a novel strategy for further improving energy efficiency by considering ternary state transceivers for an AeBSs. Using the three state model, we propose a Markovian Decision process (MDP) based algorithm, which intelligently switches between the states of the transceivers based on the offered traffic whilst maintaining a prescribed minimum channel rate per user. We have defined a reward function for the MDP, which helps us to get an optimal policy for selecting a particular mode for the transceivers of the AeBS. Considering an aerial BS with state changeable transceivers, we perform simulations to analyse the performance of the algorithm. Our results show that, around 40% gain in the energy efficiency is achieved while using our proposed MDP algorithm together with the three-state transceiver model compared to the always active mode. We also show the energy-delay tradeoff in order to design an efficient aerial base station.
Nahina Islam; Kandeepan Sithamparanathan; Karina Gomez Chavez; James Scott; Hamid Eltom. Energy efficient and delay aware ternary-state transceivers for aerial base stations. Digital Communications and Networks 2018, 5, 40 -50.
AMA StyleNahina Islam, Kandeepan Sithamparanathan, Karina Gomez Chavez, James Scott, Hamid Eltom. Energy efficient and delay aware ternary-state transceivers for aerial base stations. Digital Communications and Networks. 2018; 5 (1):40-50.
Chicago/Turabian StyleNahina Islam; Kandeepan Sithamparanathan; Karina Gomez Chavez; James Scott; Hamid Eltom. 2018. "Energy efficient and delay aware ternary-state transceivers for aerial base stations." Digital Communications and Networks 5, no. 1: 40-50.
The energy efficiency of cellular base stations is known to be improved by having the base station in sleep modes whenever possible. In this paper we present our study on ternary state transceivers for cellular base stations for further improving the energy efficiency. We consider transceivers that are capable of switching between sleep, stand-by and active modes whenever required. the ternary state transceiver is modeled as a three-state Markov process and we present an algorithm to intelligently change the states of the transceivers based on the offered traffic to the base station whilst maintaining a prescribed minimum rate per user. We present simulation results considering a typical macro base station with state changeable transceivers. Our results show that it is possible to significantly improve the energy efficiency of the base station using the proposed algorithm and further show that the algorithm approaches steady state conditions for the range of parametric values that we consider in our study.
Nahina Islam; Sithamparanathan Kandeepan; James Scott. Energy efficiency of cellular base stations with ternary-state transceivers. 2015 9th International Conference on Signal Processing and Communication Systems (ICSPCS) 2015, 1 -7.
AMA StyleNahina Islam, Sithamparanathan Kandeepan, James Scott. Energy efficiency of cellular base stations with ternary-state transceivers. 2015 9th International Conference on Signal Processing and Communication Systems (ICSPCS). 2015; ():1-7.
Chicago/Turabian StyleNahina Islam; Sithamparanathan Kandeepan; James Scott. 2015. "Energy efficiency of cellular base stations with ternary-state transceivers." 2015 9th International Conference on Signal Processing and Communication Systems (ICSPCS) , no. : 1-7.
In this paper we analyse the energy efficiency of MQAM and MFSK for short range wireless transmissions, up to a few 100's of meters, and propose optimum rate adaptation to minimize the energy dissipation during transmissions under different channel environment. Energy consumed for transmitting the data over a distance to maintain a prescribed error probability together with the circuit energy have been considered in our work. Our results indicate that the energy efficiency can be significantly improved by performing optimal rate adaptation given the radio and channel parameters, and furthermore we identify the maximum distance where optimal rate adaptation can be performed beyond which the optimum rate then becomes the same as the minimum data rate.
Nahina Islam; Sithamparanathan Kandeepan; James Scott. Optimal rate adaptation for energy efficiency with MQAM and MFSK. 2014 International Symposium on Wireless Personal Multimedia Communications (WPMC) 2014, 328 -334.
AMA StyleNahina Islam, Sithamparanathan Kandeepan, James Scott. Optimal rate adaptation for energy efficiency with MQAM and MFSK. 2014 International Symposium on Wireless Personal Multimedia Communications (WPMC). 2014; ():328-334.
Chicago/Turabian StyleNahina Islam; Sithamparanathan Kandeepan; James Scott. 2014. "Optimal rate adaptation for energy efficiency with MQAM and MFSK." 2014 International Symposium on Wireless Personal Multimedia Communications (WPMC) , no. : 328-334.