Name
Title | ||
|---|---|---|
Monitoring System to Strive against Fall Armyworm in Crops Case Study: Maize in Rwanda |
Abstract | ||
|---|---|---|
The food security has received much attention due the hunger that usually affects some countries in Africa. Pests are very dangerous to crops and reduce the harvest of affected crop and can cause risk if no technical methods are applied to strive against them. Fall armyworm (FAW) is one the pest that has attacked the priority stable crop of Rwanda (maize) since last year 2017. This reduced the expected harvest from this crop. The presence of this pest costs the government to use drones and other special forces to strive for it, but pest will remain a problem if there is no regular, automatic way to detect the pest and strive for it at the early days of attacking the crop. This paper introduces a design of a prototype of an automated system that will be able to detect the presence of a fall armyworm in the field. The system will use the new technology of Internet of Things (IoT) where sensors are used to identify the pest location. Once the presence of the pest is detected in the farm, the system will be able to give the information of the affected crop and notify the farmer through his/her mobile phone who will immediately react accordingly. Through the authorization from the farmer, the system will be able to pump pesticides to kill both larvae and eggs of fall armyworm on the affected crop. This automated system will save the farmer's time, as it will monitor the crops while the farmer is occupied with other activities. Lastly the system will help to increase the production of maize in Rwanda since the crop will be safe from the pest. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/SmartWorld.2018.00046 | 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) |
Keywords | Field | DocType |
Food security,fall armyworm,Pest detection,Internet of things,sensors, maize, pest | Agricultural science,Monitoring system,Computer science,Crop,Authorization,Internet of Things,Computer network,PEST analysis,Fall armyworm,Food security | Conference |
ISBN | Citations | PageRank |
978-1-5386-9381-0 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Damien Hanyurwimfura | 1 | 10 | 3.06 |
| Eric Nizeyimana | 2 | 0 | 0.34 |
| Faustine Ndikumana | 3 | 0 | 0.34 |
| Didacienne Mukanyiligira | 4 | 0 | 0.34 |
| Abubakar Bakar Diwani | 5 | 0 | 0.34 |
| Florence Mukamanzi | 6 | 0 | 0.34 |