IOT Based Vegetable Crop Pest Prediction Using Smart Farming | [Abstract Book on International Conference on Life Sciences (ICLS-23) 11-12 May 22-23 • 2023]

Author(s):

1. Rana Muhammad Saleem: Department of Computer Science, UAF, Sub Campus Burewala, Pakistan

2. Muhammad Asif Khan: Department of Food Science and Technology,IUB, Bahawalpur, Pakistan

3. Hafiz Muhammad Haroon: Department of Computer Science, UAF, Sub Campus Burewala, Pakistan

4. Sidra Habib: Department of Computer Science, UAF, Sub Campus Burewala, Pakistan

5. Komal Nida Khan: Department of Math and Statistics, University of Agriculture, Faisalabad Sub Campus Burewala, Pakistan

6. Saba Nasir: Department of Management Science, University of Agriculture, Faisalabad Sub Campus Burewala, Pakistan

7. Sadaf Shakoor: Department of Food Science, University of Agriculture, Faisalabad Sub Campus Burewala, Pakistan

Abstract:

Insect pest have great influence in vegetable crop growth. It can be minimized by prediction of insect pest using environmental parameters, IOT and machine learning algorithms. The directly sensed environment conditions are used as input to the machine learning model to make binary decisions regarding the pest population according to the prevailing environmental conditions. After implementation in field 89.2% accuracy have achieved by using naïve bayes binary algorithm. The f1 recall, precision and support evaluation metrices have been used for algorithm evaluation. It is highly recommended for formers to increase the yield of vegetable crop.

Page(s): 31-31

DOI: DOI not available

Published: Journal: Abstract Book on International Conference on Life Sciences (ICLS-23) 11-12 May 22-23, Volume: 0, Issue: 0, Year: 2023

Keywords:

Naïve Bayes , Internet Of Things Iot , smart farming , Insect Pest Prediction

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