Ananda Maiti

UTAS Home Dr Ananda Maiti

Ananda Maiti

Information & Communication Technology

Room 110 , Building V

6226 7277 (phone)


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


DegreeThesis TitleUniversity CountryDate of Award
PhDEnabling Peer-to-Peer Remote Experimentation in Distributed Online Remote LaboratoriesUniversity of Southern Queensland (USQ)Australia2016
MSc Computer ScienceSoftware Development for Remote Laboratory Management SystemVIT UniversityVellore, India2012

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 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

KIT202 Secure Web Programming

View more on Dr Ananda Maiti in WARP


  • 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


  • 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


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)
  • Human information interaction and retrieval (461003)
  • Supply chains (350909)
  • Knowledge representation and reasoning (460206)
  • Pervasive computing (460809)
  • Computer vision (460304)
  • Service oriented computing (460612)
  • Distributed computing and systems software (460699)
  • Distributed systems and algorithms (460605)
  • Autonomous agents and multiagent systems (460202)
  • Human-computer interaction (460806)
  • Virtual and mixed reality (460708)
  • Aged health care (420301)
  • Animal growth and development (300301)
  • Separation science (340109)
  • Modelling and simulation (460207)
  • Preventative health care (420605)
  • Deep learning (461103)
  • Soil physics (410605)
  • Aquaculture (300501)
  • Intelligent robotics (460205)
  • Animal reproduction and breeding (300305)
  • Health promotion (420603)
  • Occupational and workplace health and safety (350505)
  • Cognition (520401)
  • Satisfiability and optimisation (460210)
  • 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)
  • Information systems, technologies and services (220499)
  • Other manufacturing (249999)
  • Higher education (160102)
  • Instrumentation (241099)
  • Evaluation of health outcomes (200202)
  • Applied computing (220402)
  • Injury prevention and control (200408)
  • Air quality (180101)
  • National security (140109)
  • Aquaculture oysters (100204)
  • Command, control and communications (140102)
  • Emerging defence technologies (140104)
  • Weather (180104)
  • Human-computer interaction (220407)
  • Management of water consumption by animal production (100104)
  • Rehabilitation or conservation of terrestrial environments (180604)
  • Climate change adaptation measures (excl. ecosystem) (190101)
  • Health education and promotion (200203)
  • Occupational health (200507)
  • Behaviour and health (200401)
  • Information systems (220408)


Total publications


Journal Article

(6 outputs)
2021Hoque 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 - 2Web of Science - 2

Co-authors: Hoque S; Xu S; Wei Y


2021Maiti 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: Web of Science - 1

Co-authors: Raza A; Kang BH


2020Li 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 - 22Web of Science - 19

Co-authors: Springer M; Gray T


2019Maiti 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 - 11Web of Science - 10

Co-authors: Raza A; Kang BH; Hardy L


2018Maiti 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


2018Maiti 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 - 12Web of Science - 8


Conference Publication

(3 outputs)
2019Maiti A, Byrne T, Kist AA, 'Teaching internet of things in a collaborative laboratory environment', Proceedings of the 5th Experiment@ International Conference ( 2019), 12-14 June 2019, Funchal, Portugal, pp. 193-198. (2019) [Refereed Conference Paper]

DOI: 10.1109/EXPAT.2019.8876480 [eCite] [Details]

Citations: Scopus - 5


2019Smith M, Maiti A, Maxwell A, Kist AA, 'Applying augmented reality to new or existing remote access laboratories', Proceedings of the 5th Experiment@ International Conference ( 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


2017Maiti 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 ( 2017), 6-8 June 2017, Faro, Portugal, pp. 159-164. ISBN 9781538608104 (2017) [Refereed Conference Paper]

DOI: 10.1109/EXPAT.2017.7984396 [eCite] [Details]


Grants & Funding

Funding Summary

Number of grants


Total funding



Developing the tools and articulating the value proposition for genomic selection in Pacific oyster selective breeding (2022 - 2023)$370,969
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
Fisheries Research & Development Corporation ($370,969)
Administered By
University of Tasmania
Research Team
Trotter AJ; Smith GG; Rust SA; Amin M; Maiti A; Kang BH; Garcia Lafuente JA
2022 - 2023
Autonomous Remote Drone Management System with Fixed Ground Stations (2021)$10,000
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.
Australian Antarctic Division ($10,000)
Contract Research
Administered By
University of Tasmania
Research Team
Maiti A
Smart Operation of the Greyscan ETD 100 in Laboratory User Interface Mode (2021)$65,729
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 worlds 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.
Australian Federal Police ($65,729)
Contract Research
Administered By
University of Tasmania
Research Team
Breadmore MC; Kang BH; Amin M; Maiti A
Drought Resilience Tasmania - Actionable Knowledge and Solutions for Sustainable Prosperity (2021 - 2024)$9,530,969
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 Tasmaniashigh-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.
Department of Agriculture Water and the Environment ($9,530,969)
Future Drought Fund
Administered By
University of Tasmania
Research Team
Evans KJ; Mohammed CL; Kumar S; Field B; Harris R; Jones ME; Anders RJ; Higgins VJ; Bryant M; Harrison MT; Gracie AJ; Wilson MD; Jordan GJ; O'Reilly-Wapstra JM; Barmuta LA; Remenyi TA; Kang BH; Amin M; Maiti A; Fraser SP; Kilpatrick SI; Barnes NR; Beasy KM; Coleman BJ; Stoeckl NE; D'Alessandro SP; Tian J; Chuah S; Norris K; Ferguson SG; Auckland SRJ
2021 - 2024
AI in a box: A proof-of-concept for Tasmania giant crabs detection and gender classification. (2021)$24,995
University of Tasmania ($24,995)
Administered By
University of Tasmania
Research Team
Tran SN; Maiti A; Hadley SA
Visualization of Digital Twins for Internet-of-Things with Blockchain technology (2020)$2,375
University of Tasmania ($2,375)
Administered By
University of Tasmania
Research Team
Chinthammit W; Maiti A

Research Supervision




PhDDeep Learning-based Absolute Pose Estimation of On-road Vehicles for Autonomous Driving2019
PhDDevelopment and Evaluation of an Intelligent Student Assessment System in a Remote Laboratory for Embedded Systems Education (RLESE)2020
PhDIoT Data Quality Management2020