Evidence map›Paper›PMID 36433502›Full record

ArticleSensors (Basel, Switzerland)2022

Monitoring Ambient Parameters in the IoT Precision Agriculture Scenario: An Approach to Sensor Selection and Hydroponic Saffron Cultivation.

Kanwalpreet Kour, Deepali Gupta, Kamali Gupta, Divya Anand, Dalia H Elkamchouchi, Cristina Mazas Pérez-Oleaga, Muhammad Ibrahim, Nitin Goyal

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
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

8 authors.

Kanwalpreet KourChitkara University Institute of Engineering & Technology, Chitkara University, Rajpura 140401, Punjab, India.
Deepali GuptaChitkara University Institute of Engineering & Technology, Chitkara University, Rajpura 140401, Punjab, India.ORCID 0000-0002-3207-5248
Kamali GuptaChitkara University Institute of Engineering & Technology, Chitkara University, Rajpura 140401, Punjab, India.
Divya AnandSchool of Computer Science and Engineering, Lovely Professional University, Phagwara 144411, Punjab, India.ORCID 0000-0003-4915-8426
Dalia H ElkamchouchiDepartment of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.ORCID 0000-0002-9533-3179
Cristina Mazas Pérez-OleagaResearch and Innovation, Universidad Europea del Atlántico, C/Isabel Torres 21, 39011 Santander, Spain.
Muhammad IbrahimDepartment of Computer Engineering and Research Center of Advance Technology, Jeju National University, Jeju-si 63243, Republic of Korea.ORCID 0000-0001-8729-8759
Nitin GoyalDepartment of Computer Science and Engineering, Central University of Haryana, Mahenderagarh 123031, Haryana, India.ORCID 0000-0001-7878-363X

Funding

Princess Nourah bint Abdulrahman University PNURSP2022R120
6 · The paper itself

Abstract

The world population is on the rise, which demands higher food production. The reduction in the amount of land under cultivation due to urbanization makes this more challenging. The solution to this problem lies in the artificial cultivation of crops. IoT and sensors play an important role in optimizing the artificial cultivation of crops. The selection of sensors is important in order to ensure a better quality and yield in an automated artificial environment. There are many challenges involved in selecting sensors due to the highly competitive market. This paper provides a novel approach to sensor selection for saffron cultivation in an IoT-based environment. The crop used in this study is saffron due to the reason that much less research has been conducted on its hydroponic cultivation using sensors and its huge economic impact. A detailed hardware-based framework, the growth cycle of the crop, along with all the sensors, and the block layout used for saffron cultivation in a hydroponic medium are provided. The important parameters for a hydroponic medium, such as the concentration of nutrients and flow rate required, are discussed in detail. This paper is the first of its kind to explain the sensor configurations, performance metrics, and sensor-based saffron cultivation model. The paper discusses different metrics related to the selection, use and role of sensors in different IoT-based saffron cultivation practices. A smart hydroponic setup for saffron cultivation is proposed. The results of the model are evaluated using the AquaCrop simulator. The simulator is used to evaluate the value of performance metrics such as the yield, harvest index, water productivity, and biomass. The values obtained provide better results as compared to natural cultivation.

Indexed as

CrocusAgricultureBiomassCrops, AgriculturalHydroponicshydroponicsIoTNFTprecision agriculturesaffronsensorssmart farming

Identifiers

PMID36433502
PMCPMC9697548

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.