Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

KPI Deployment for Enhanced Rice Production in a Geo-Location Environment using a Wireless Sensor Network

Domaine:

agriculturedigital infrastructure

Type de record:

paper
Créateur:
Oyi
Éditeur:
Zenodo
Hôte:avatar
Rice production plays a significant role in food security in the globe. The automation of rice production remains the paradigm shift to meet up with the consumer demand considering the tremendous increase in consumption rate. The paper aimed at implementing some selected key performance indicators (KPIs) for enhanced rice production by addressing five major challenges that face rice farmers, especially in Nigeria. The Non-availability of water/rain for year-round cultivation, disproportionate application of fertilizer, weed control/prevention, pest/disease control, and rodents and bird’s invasion are outlined as observed constraints. A Zigbee-based Enhanced Wireless Sensor Network (eWSN) was used to model various network scenarios to demonstrate data sensing of different environmental variables in a given farm land. This was achieved by varying network devices at different scenarios using OPNET simulator and understudying the network performances. Each new set of network devices was integrated to a Zigbee Coordinator (ZC) which assigns an address to its members and forms a personal area network (PAN), thus representing data sensing of a particular environmental variable. Three different scenarios were designed and simulated in the study. Each of the temperature and humidity, motion and soil nutrient sensors generated about 29bps of traffic. At the Coordinators, steady stream of traffic was received. The temperature and humidity Coordinators, received a traffic of 64bps each, while the soil nutrient Coordinator received data traffic of 96bps. The outcome of the design demonstrates effective communication between different network components and provides insight on how WSN could be used simultaneously to monitor a number of different environmental variables on a farm field. By implementing the KPIs, the simulation result provided an estimated yield increase from 2.2 to 8.7 metric ton per hectare of a rice farm.

Visit

doi.orgzenodo.org

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcodeOpen Accessinfo:eu-repo/semantics/openAccess

Similaires

An Enhanced Geo Location Technique for Social Network Communication SystemA Wireless Sensor Network Air Pollution Monitoring SystemDesign of a Security Wireless Sensor Network for Emergency Response Centers (SWiSNERC)Wildfire Monitoring and Detection System Using Wireless Sensor Network: A Case Study of TanzaniaA new generalized stochastic Petri net modeling for energy‐harvesting‐wireless sensor network assessmentNode coloring in a wireless sensor network with unidirectional links and topology changes

An Enhanced Geo Location Technique for Social Network Communication System

Social networks have become very popular in recent years because of the increasing large number and

A Wireless Sensor Network Air Pollution Monitoring System

Sensor networks are currently an active research area mainly due to the potential of their applicati

Design of a Security Wireless Sensor Network for Emergency Response Centers (SWiSNERC)

The design and implementation of a security wireless sensor network capable of detecting physica

Wildfire Monitoring and Detection System Using Wireless Sensor Network: A Case Study of Tanzania

A new generalized stochastic Petri net modeling for energy‐harvesting‐wireless sensor network assessment

Summary This paper proposes an energy‐harvesting‐aware model that aims to assess the performances o

Node coloring in a wireless sensor network with unidirectional links and topology changes

International audience In wireless sensor networks, energy efficiency is achieved by