Evidence map›Paper›PMID 37896565›Full record

ArticleSensors (Basel, Switzerland)2023

Smart Crop Cultivation System Using Automated Agriculture Monitoring Environment in the Context of Bangladesh Agriculture.

Md Bayazid Rahman, Joy Dhon Chakma, Abdul Momin, Shahidul Islam, Md Ashraf Uddin, Md Aminul Islam, Sunil Aryal

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
5.2field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 13 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 3 countries.

Md Bayazid RahmanDepartment of Computer Science and Engineering, Faculty of Science and Technology, Notre Dame University Bangladesh, Dhaka 1000, Bangladesh.ORCID 0000-0003-4578-8682
Joy Dhon ChakmaDepartment of Computer Science and Engineering, Faculty of Science and Technology, Notre Dame University Bangladesh, Dhaka 1000, Bangladesh.ORCID 0000-0002-4775-4470
Abdul MominAgricultural Engineering Technology, School of Agriculture, Tennessee Tech University, Cookeville, TN 38505, USA.ORCID 0000-0002-3139-5274
Shahidul IslamDepartment of Agriculture, University of Arkansas at Pine Bluff, Pine Bluff, AR 71601, USA.
Md Ashraf UddinSchool of Information Technology, Deakin University, Geelong, VIC 3220, Australia.ORCID 0000-0002-4316-4975
Md Aminul IslamDepartment of Computer Science and Engineering, Jagannath University, Dhaka 1100, Bangladesh.ORCID 0000-0002-4507-8130
Sunil AryalSchool of Information Technology, Deakin University, Geelong, VIC 3220, Australia.ORCID 0000-0002-6639-6824
Deakin University · AUJagannath University · BDTennessee Technological University · USUniversity of Arkansas at Pine Bluff · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Internet of Things (IoT) is a transformative technology that is reshaping industries and daily life, leading us towards a connected future that is full of possibilities and innovations. In this paper, we present a robust framework for the application of Internet of Things (IoT) technology in the agricultural sector in Bangladesh. The framework encompasses the integration of IoT, data mining techniques, and cloud monitoring systems to enhance productivity, improve water management, and provide real-time crop forecasting. We conducted rigorous experimentation on the framework. We achieve an accuracy of 87.38% for the proposed model in predicting data harvest. Our findings highlight the effectiveness and transparency of the framework, underscoring the significant potential of the IoT in transforming agriculture and empowering farmers with data-driven decision-making capabilities. The proposed framework might be very impactful in real-life agriculture, especially for monsoon agriculture-based countries like Bangladesh.

Indexed as

AgricultureTechnologyBangladeshcrop monitoringcrop yield predictiondecision tree classifierirrigation controlsmart agriculture

Identifiers

PMID37896565
PMCPMC10611150
OpenAlexW4387653717

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.