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Record W3185318264 · doi:10.22214/ijraset.2021.36625

Military Safety and Surveillance Robot with Two-Way Communication

2021· article· en· W3185318264 on OpenAlexaff
Vinod Kumar S

Bibliographic record

VenueInternational Journal for Research in Applied Science and Engineering Technology · 2021
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsArduinoBattlefieldRobotWirelessComputer scienceReal-time computingUnmanned ground vehicleTransmission (telecommunications)Radio frequencyTeleroboticsTelecommunicationsEmbedded systemArtificial intelligenceMobile robot

Abstract

fetched live from OpenAlex

This paper focuses on developing an Unmanned Ground Vehicle (UGV) wireless robot. It can sense the different parameters of the surroundings; transmit the data through a wireless medium and display data in LCD as well as on a Remote PC. It controls the direction of the robot from a remote location using wireless communication and thereby performing military surveillance and analysing the battlefield environment and challenges that the soldiers may potentially face. By using a Wi-Fi camera and many sensors the robot can help the soldiers in the war fields to examine various environmental conditions and challenges. The arduino and NRF (Nordic Radio Frequency) technologies are used to achieve the above tasks. The different sensors and the robotic arm are connected to the Arduino Uno which in turn is connected to the Nordic Radio Frequency module. Data transmission and receiving are done through Nordic Radio Frequency communication technology. The proposed model eliminates the limitations of the existing models and thus provides better assistance to the soldiers and enables them to handle their missions better.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.670
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.323
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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