Feature Article: Smart Cities A Decision Support Benchmark for Forecasting the Consumption of Agriculture Stocks Najam Ul Hassan, Farrukh Zeeshan Khan, and Hafsa Bibi University of Engineering and Technology Nokhaiz Tariq Khan Riphah School of Business Management Anand Nayyar Duy Tan University Muhammad Bilal Hankuk University of Foreign Studies Abstract-Agricultural industry contributes to the economic backbone of many countries. Major crops like wheat, cotton, and rice stand out as fulfillment for basic commodities as well as profitable crops. Naturally, the consumption of major crops is increasing every year, influencing many countries to import the staple crops to meet the nutritional requirements of individuals, and thereby, keeping pressure on the economies for the years ahead. This research work addresses the development of an accurate consumption forecasting model for time series data. The proposed methodology uses 18 socioeconomic and environmental factors and evaluates their impact on major crop consumption in Pakistan. Most influential factors are differentiated by the Linear Regression Model to forecast next year's upshot. The smart results of the model are beneficial for the farmers to cope with the decisive question of next pragmatic crop. The Digital Object Identifier 10.1109/MCE.2021.3063547 Date ofpublication 3 March 2021; date ofcurrent version 6 October 2021. November/December 2021 Published by the IEEE Consumer Technology Society 2162-2248 ß 2021 IEEE 45