Measuring various features such as temperature, humidity, light intensity (E), pH levels, carbon dioxide concentration (CO2), plant height, and plant health at frequent intervals using supervised machine learning, particularly logistic regression, can indeed provide insights into predicting successful lettuce leafy green harvests. However, the accuracy of such predictions may vary depending on several factors, including the quality and quantity of data, feature selection, and model complexity.

Since the publication of the previous article, numerous developments have taken place. We have successfully achieved certification as blockchain developers for our Blockchain Project Leads. Additionally, we are delighted to share that we've introduced two new blockchain projects: "hashrepos," featuring an ERC-721 smart contract, and "room4all," incorporating various web3 functionalities.