Profiles
Ananda Maiti

Ananda Maiti
Lecturer
Information & Communication Technology
Room 110 , Building V
+61 3 6226 7277 (phone)
Biography
Ananda is an early career researcher. He completed my PhD in 2016. His current research interests include Computer Networking, Algorithms along with Internet-of-Things and its various applications in agriculture and remote laboratories. Ananda is also interested in augmented and virtual reality and their application in e-learning.
Career summary
Qualifications
Degree | Thesis Title | University | Country | Date of Award |
---|---|---|---|---|
PhD | Enabling Peer-to-Peer Remote Experimentation in Distributed Online Remote Laboratories | University of Southern Queensland (USQ) | Australia | 2016 |
MSc Computer Science | Software Development for Remote Laboratory Management System | VIT University | Vellore, India | 2012 |
Administrative expertise
- 2016 – Now Associate Editor for International Journal of Online Engineering
- 2014 – Now Member of International Program Committee of the Remote Engineering and Virtual Instrumentation Conference
Teaching
Teaching expertise
- 2014-2018 Computer Systems and Communications Protocol, USQ
- Assisted with developing course materials for a MOOC
- Teaching and curriculum development in several courses at USQ
Teaching responsibility
View more on Dr Ananda Maiti in WARP
Expertise
- Developed control systems models for IoT systems
- Remote Laboratories for Engineering Education
- Developed algorithms to extract and convert radar related data using Python.
Research Themes
Internet of Things, Algorithms, Web Programming, Instrumentation, data mining
Collaboration
- 2016-Now Collaboration on remote laboratories with members of the International Association of Online Engineering (IAOE).
- 2017-Now Collar design for wild animals with wildlife experts at USQ
Awards
2015 University of Southern Queensland Research Publication Excellence Award
Current projects
Animal Engagement using Wave machine with Zoo Victoria
Fields of Research
- Cyberphysical systems and internet of things (460603)
- Supply chains (350909)
- Human information interaction and retrieval (461003)
- Knowledge representation and reasoning (460206)
- Intelligent robotics (460205)
- Pervasive computing (460809)
- Service oriented computing (460612)
- Distributed computing and systems software (460699)
- Computer vision (460304)
- Distributed systems and algorithms (460605)
- Autonomous agents and multiagent systems (460202)
- Environmental assessment and monitoring (410402)
- Human-computer interaction (460806)
- Virtual and mixed reality (460708)
- Pattern recognition (460308)
- Aged health care (420301)
- Separation science (340109)
- Modelling and simulation (460207)
- Animal growth and development (300301)
- Deep learning (461103)
- Preventative health care (420605)
- Soil physics (410605)
- Occupational and workplace health and safety (350505)
- Aquaculture (300501)
- Animal reproduction and breeding (300305)
- Health promotion (420603)
- Satisfiability and optimisation (460210)
- Cognition (520401)
- Planning and decision making (460209)
- Farm management, rural management and agribusiness (300208)
Research Objectives
- Teaching and instruction technologies (160304)
- Artificial intelligence (220403)
- Technological and organisational innovation (150306)
- Behaviour and health (200401)
- Rehabilitation or conservation of terrestrial environments (180604)
- Administration and business support services (110301)
- Information systems, technologies and services (220499)
- Evaluation of health outcomes (200202)
- Other manufacturing (249999)
- Higher education (160102)
- Instrumentation (241099)
- Assessment and management of terrestrial ecosystems (180601)
- Native forests (260204)
- National security (140109)
- Aquaculture oysters (100204)
- Management of water consumption by animal production (100104)
- Applied computing (220402)
- Injury prevention and control (200408)
- Human-computer interaction (220407)
- Command, control and communications (140102)
- Air quality (180101)
- Weather (180104)
- Emerging defence technologies (140104)
- Health education and promotion (200203)
- Climate change adaptation measures (excl. ecosystem) (190101)
- Occupational health (200507)
- Information systems (220408)
Publications
Total publications
11
Journal Article
(8 outputs)Year | Citation | Altmetrics |
---|---|---|
2023 | Hoque S, Xu S, Maiti A, Wei Y, Arafat MY, 'Deep learning for 6D pose estimation of objects A case study for autonomous driving', Expert Systems With Applications: An International Journal, 223 Article 119838. ISSN 0957-4174 (2023) [Refereed Article] DOI: 10.1016/j.eswa.2023.119838 [eCite] [Details] Co-authors: Hoque S; Xu S; Wei Y | |
2023 | Maiti A, Ye A, Schmidt M, Pedersen S, 'A privacy-preserving desk sensor for monitoring healthy movement breaks in smart office environments with the internet of things', Sensors, 23 Article 2229. ISSN 1424-8220 (2023) [Refereed Article] DOI: 10.3390/s23042229 [eCite] [Details] Co-authors: Ye A; Schmidt M; Pedersen S | |
2021 | Hoque S, Arafat M, Xu S, Maiti A, Wei Y, 'A comprehensive review on 3D object detection and 6D pose estimation with deep learning', IEEE Access, 9 pp. 143746-143770. ISSN 2169-3536 (2021) [Refereed Article] DOI: 10.1109/ACCESS.2021.3114399 [eCite] [Details] Citations: Scopus - 11Web of Science - 5 Co-authors: Hoque S; Xu S; Wei Y | |
2021 | Maiti A, Raza A, Kang BH, 'Teaching embedded systems and Internet-of-Things supported by multipurpose multiobjective remote laboratories', IEEE Transactions on Learning Technologies, 14, (4) pp. 526-539. ISSN 1939-1382 (2021) [Refereed Article] DOI: 10.1109/TLT.2021.3104258 [eCite] [Details] Citations: Scopus - 2Web of Science - 1 Co-authors: Raza A; Kang BH | |
2020 | Li J, Maiti A, Springer M, Gray T, 'Blockchain for supply chain quality management: challenges and opportunities in context of open manufacturing and industrial internet of things', International Journal of Computer Integrated Manufacturing, 33, (12) pp. 1321-1355. ISSN 0951-192X (2020) [Refereed Article] DOI: 10.1080/0951192X.2020.1815853 [eCite] [Details] Citations: Scopus - 40Web of Science - 35 Co-authors: Li J; Springer M; Gray T | |
2019 | Maiti A, Raza A, Kang BH, Hardy L, 'Estimating service quality in industrial internet-of-things monitoring applications with blockchain', IEEE Access, 7 pp. 155489-155503. ISSN 2169-3536 (2019) [Refereed Article] DOI: 10.1109/ACCESS.2019.2948269 [eCite] [Details] Citations: Scopus - 14Web of Science - 11 Co-authors: Raza A; Kang BH; Hardy L | |
2018 | Maiti A, Kist AA, Maxwell AD, 'Automata-based generic model for interoperating context-aware ad-hoc devices in Internet of Things', IEEE Internet of Things Journal, 5, (5) pp. 3837-3852. ISSN 2327-4662 (2018) [Refereed Article] DOI: 10.1109/JIOT.2018.2872117 [eCite] [Details] Citations: Scopus - 2Web of Science - 1 | |
2018 | Maiti A, Zutin DG, Wuttke H-D, Henke K, Maxwell AD, et al., 'A framework for analyzing and evaluating architectures and control strategies in distributed remote laboratories', IEEE Transactions on Learning Technologies, 11, (4) pp. 441-455. ISSN 1939-1382 (2018) [Refereed Article] DOI: 10.1109/TLT.2017.2787758 [eCite] [Details] Citations: Scopus - 15Web of Science - 11 |
Conference Publication
(3 outputs)Year | Citation | Altmetrics |
---|---|---|
2019 | Maiti A, Byrne T, Kist AA, 'Teaching internet of things in a collaborative laboratory environment', Proceedings of the 5th Experiment@ International Conference (exp.at 2019), 12-14 June 2019, Funchal, Portugal, pp. 193-198. (2019) [Refereed Conference Paper] DOI: 10.1109/EXPAT.2019.8876480 [eCite] [Details] Citations: Scopus - 6 | |
2019 | Smith M, Maiti A, Maxwell A, Kist AA, 'Applying augmented reality to new or existing remote access laboratories', Proceedings of the 5th Experiment@ International Conference (exp.at 2019), 12-14 June 2019, Funchal, Portugal, pp. 6-11. (2019) [Refereed Conference Paper] DOI: 10.1109/EXPAT.2019.8876551 [eCite] [Details] Citations: Scopus - 1 | |
2017 | Maiti A, Maxwell AD, Kist AA, 'Using marker based augmented reality and natural user interface for interactive remote experiments', Proceedings of the 4th Experiment@ International Conference (exp.at 2017), 6-8 June 2017, Faro, Portugal, pp. 159-164. ISBN 9781538608104 (2017) [Refereed Conference Paper] |
Grants & Funding
Funding Summary
Number of grants
8
Total funding
Projects
- Description
- The project assesses traceability RegTech applications that can be used by different producers, compliance agencies, and logistics providers in the Australian honey bee and cherry industries. Working with project partners and stakeholders in the two industries, the project will 1) investigate how existing traceability technology use may support RegTech applications and how RegTech in turn can strengthen existing traceability systems; 2) assess areas of regulations, rules, codes of practice and other compliance requirements where RegTech may be applied to assist compliance obligations in the two industries; and 3) analyse the cost-benefit of RegTech applications and identify a roadmap for adoption. The outcomes of the project will provide insights into the feasibility of traceability RegTech applications in the two industries, the readiness, and roadmap for adoption for the Australian honey bee and cherry industries and their related supply chains. The project will contribute to enhancing agricultural traceability reforms, and supporting growth of the agricultural sector.
- Funding
- Department of Agriculture, Fisheries and Forestry ($333,649)
- Scheme
- Traceability Grant
- Administered By
- University of Tasmania
- Research Team
- Fei J; Maiti A
- Period
- 2023 - 2024
- Description
- The UTAS Active Work Laboratory builds and evaluates digital solutions designed to address sedentary behaviour at work. These industry-focussed solutions enable employees to re-introduce movement into their everyday work routines helping to prevent the early onset of disease and disability. This project was developed to progress our commercialisation opportunities within the State and beyond to national and international audiences.
- Funding
- University of Tasmania ($11,340)
- Scheme
- null
- Administered By
- University of Tasmania
- Research Team
- Pedersen SJ; Schmidt M; Maiti A; Ghosh B
- Year
- 2023
- Description
- he Chemical Criminalistics (CC) team at the Australian Federal Police (AFP) performs a range of examinations on chemical trace evidence to support numerous internal and external stakeholders. In addition to the traditional laboratory capabilities (using benchtop instruments), CC also provides a deployable capability, including portable identification instruments and a mobile laboratory. This function can be deployed locally, nationally and internationally and is particularly critical in the field of explosives analysis. Rapid deployments are often required in support of counter terrorism operations, where the CC team is able to conduct trace organic and trace inorganic explosive detection outside of the laboratory environment. The CC team acquired x2 GreyScan ETD-100 units in late 2019. The UTAS-based and Australian manufactured ETD-100 is the world's first automated explosive trace detection device designed to detect inorganic explosives based on nitrates, chlorates and perchlorates. The ETD-100 was designed to complement the current security screening technology at points-of entry such as airport checkpoints and aviation cargo screening. The CC team have undertaken an extensive validation of the ETD-100 and established a number of limitations in its current (security screening) end-user form. During the validation process, the CC team established that it was possible to adopt this new technology and make it more relevant to AFP forensic operations. In particular, it is possible to interface the ETD-100 with a laptop utilising a customised Laboratory User Interface. In this mode, the analyst is able to interrogate the data coming off the box to allow a more informed decision to be made (other than just the current PASS or WARNING screens). Further development is required to the interface to provide the analyst with the ability to detect and identify other relevant analytes of forensic interest other than the three currently programmed explosive ingredient targets (namely: nitrates, chlorates, perchlorates), which will be developed in this project. This enhanced capability is considered critical when undertaking chemical exploitation in support of the frontline response to explosive incidents and intelligence-led disruptions.
- Funding
- Australian Federal Police ($65,729)
- Scheme
- Contract Research
- Administered By
- University of Tasmania
- Research Team
- Breadmore MC; Kang BH; Amin M; Maiti A
- Year
- 2022
- Description
- Genomic selection is a new applied breeding technology that is being used in commercial animal and plant breeding programwith significant, and times large, economic benefits. However, there are no commercial applications in oyster breeding. Genomic selection requiressignificant increase in costs due to the need to genotyping large numbers of individuals, and there are technical and logistical challenges in applying thitechnology to oyster breeding. This project is a preliminary step intended to demonstrate an economic cost benefit, evaluate genotyping toolsmethodology development, proof of conceptfor phenotyping, thereby providing information to assist a decision aboutmoving thisto operational breeding
- Funding
- Fisheries Research & Development Corporation ($370,969)
- Scheme
- Grant
- Administered By
- University of Tasmania
- Research Team
- Trotter AJ; Smith GG; Rust SA; Amin M; Maiti A; Kang BH; Garcia Lafuente JA
- Period
- 2022 - 2023
- Description
- Antarctica is a vast region with various landscape and terrain features. It is also one the most remote areas lacking telecommunication infrastructure. Also, solar conditions make difficult to harvest solar power for remotely operated devices. Due to lack of power and communication infrastructure, it is necessary to have an optimal and dynamic sensor network to collect information back by a mobile communication framework.A combination of Fixed Ground Based stations (FGS) and drones can be used to collect a variety of data from a wide range of environments dynamically. Several key factors need to be addressed in order to exchange information between the nodes. If a certain area of the network needs any specific attention, then drones must be initialized and dispatched immediately.This project will create an autonomous remote drone management system that will simulate a large area and make decisions regarding when and how to dispatch the drones based on time, space and radio connectivity properties.
- Funding
- Australian Antarctic Division ($10,000)
- Scheme
- Contract Research
- Administered By
- University of Tasmania
- Research Team
- Maiti A
- Year
- 2021
- Description
- Water is a major asset for Tasmania linked to livelihoods, energy production, irrigated and rainfed agriculture, environmental management and conservation. Competing demands forwater intensify during droughts and as hot and dry years increase in number. Wise and fair water management requires a multi-stakeholder partnership to innovate for droughtresilience, optimal water management and self-reliance. Our Hub will enable drought preparedness in Tasmania through collective and co-designed actions that sustain Tasmania'shigh-value, clean, green international brand. We will engage with local knowledge and land stewardship through a deliberate and negotiated process and uphold the rights ofTasmanian Aboriginal people to benefit from innovations they enable. The Hub, for the first time, brings together the major players - farmers, land and water managers, researchers,and indigenous knowledge owners - who, together can reduce the risks associated with drought in Tasmania.
- Funding
- Department of Agriculture Water and the Environment ($9,530,969)
- Collaborators
- East Coast Primary Producers Association ($3,000); HEAL COUNTRY PTY LTD ($80,040); Private Forests Tasmania ($50,000); The Derwent Catchment Project Inc ($50,000)
- Scheme
- Future Drought Fund
- Administered By
- University of Tasmania
- Research Team
- Knowles SG; Mohammed CL; Kumar S; Field B; Jones ME; Anders RJ; Higgins VJ; Bryant M; Harrison MT; Gracie AJ; Wilson MD; Jordan GJ; O'Reilly-Wapstra JM; Barmuta LA; Kang BH; Amin M; Maiti A; Fraser SP; Kilpatrick SI; Barnes NR; Beasy KM; Coleman BJ; Stoeckl NE; Tian J; Chuah S; Norris K; Ferguson SG; Auckland SRJ; Evans KJ
- Period
- 2021 - 2024
- Funding
- University of Tasmania ($24,995)
- Scheme
- null
- Administered By
- University of Tasmania
- Research Team
- Tran SN; Maiti A; Hadley SA
- Year
- 2021
- Funding
- University of Tasmania ($2,375)
- Scheme
- null
- Administered By
- University of Tasmania
- Research Team
- Chinthammit W; Maiti A
- Year
- 2020
Research Supervision
Current
6
Completed
1
Current
Degree | Title | Commenced |
---|---|---|
PhD | Deep Learning-based Absolute Pose Estimation of On-road Vehicles for Autonomous Driving | 2019 |
PhD | IoT Data Quality Management | 2020 |
PhD | Cooperative Air-ground Multiple Drone System for Unknown Environment Explorations | 2022 |
PhD | Self Diagnostic Systems for IIoT | 2022 |
Masters | Using localised smart sensing for eHealth solutions in post-COVID work environments | 2022 |
PhD | Traceability RegTech applications in the Australian Agricultural Industry | 2023 |
Completed
Degree | Title | Completed |
---|---|---|
PhD | Development and Evaluation of an Intelligent Student Assessment System in a Remote Laboratory for Embedded Systems Education (RLESE) Candidate: Leandro Disiuta | 2022 |