Recently, many companies have substituted human labor with robotics. Some farmers are sharing different perspectives on the incorporation of technology into farming techniques. Some are willing to accept the technology, some are hesitant and bemused to adapt modern technology, and others are uncertain and are worried about the potential of technology to cause havoc and decrease yields. The third group prevails the most in the developed world, for lack of know-how, including translation of utility and, most significantly, the expense involved. A special Smart Tillage platform is established to solve the above issues. A smart-engine-based decision has been developed, which further uses classification and regression trees to shift towards decision-making. The decision is focused entirely on different input factors, such as type of crop, time/month of harvest, type of plant required for the crop, type of harvest, and authorised rental budget. Sitting on top of this would be a recommendation engine that is powered by deep learning network to suggest the escalation of a farmer from lower to higher category, namely, small to medium to large. A metaheuristic is one of the best computing techniques that help for solving a problem without the exhaustive application of a procedure. Recommendations will be cost-effective and suitable for an escalating update depending on the use of sufficient amends, practices, and services. We carried out a study of 562 agriculturists. Owing to the failure to buy modern equipment, growers are flooded by debt. We question if customers will be able to rent and exchange appliances. The farmers would be able to use e-marketplace to develop their activities.

中文翻译：

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基于元启发式和机器学习的农业设备租赁和共享智能引擎

最近，许多公司已经用机器人技术代替了人工。一些农民对将技术纳入耕作技术有不同的看法。有些人愿意接受这项技术，有些人犹豫不决，无法适应现代技术，而另一些人则不确定，并担心技术可能造成严重破坏并降低产量。第三类在发达国家占主导地位，这是因为缺乏专门知识，包括实用程序的翻译，最重要的是所涉及的费用。建立了专门的智能耕种平台来解决上述问题。已经开发了基于智能引擎的决策，该决策进一步使用分类树和回归树转向决策。该决定完全集中在不同的输入因素上，例如农作物类型，收获时间/月，作物所需的植物类型，收获类型以及授权的租金预算。位于此之上的是一个推荐引擎，该引擎由深度学习网络提供动力，以建议农民从低级到高级（即，从小到中到大）的升级。元启发式算法是最好的计算技术之一，可帮助您解决问题，而无需详尽应用程序。建议将具有成本效益，并且适合根据不断更新的更新，具体取决于对足够的修改，做法和服务的使用。我们对562位农业学家进行了研究。由于无法购买现代设备，种植者被债务充斥。我们质疑客户是否能够租用和更换电器。农民将能够使用电子市场来发展他们的活动。