Plants plays a vital role in the environment because it provides the health support through absorbing the carbon dioxide and releasing the oxygen to the atmosphere. Although, it required to maintain the proper plant growth and health as well as provide the appropriate monitoring. To overcome these concerns, an Artificial Intelligence (AI) and Internet of Things (IoT) based solution is proposed to monitor the plant’s growth and health. This study demonstrates the real-time monitoring of the plants via environmental sensors such as DHT 11 and soil moisture sensors. Real-time values stored in the cloud server and applied the machine learning models to predict the plant’s growth. The Statistical parameters such as RMSE, MAE are used to analyze the resulting outcome from the system.

owadays, waste management has become a critical issue for the environment. Government and private agencies need to take certain action for proper management and cleanliness. The absence of systematic waste management system creates many issues for the environment and living creatures. Research on the Internet of Things (IoT) applications widely increased in many sectors. The waste management system is also one of the sectors. Therefore, in this study, IoT based waste monitoring system called Cloudbinis proposed to reduce the waste garbage from urban areas. In this system, Ultrasonic sensor is fixed on the top of the waste bin to monitor the level of garbage inside the bin and connected to the Blynk server. In addition, a GPS module is also employed to check the location of Waste Bin. Methane detection from garbage is an important feature in the system. Results show that the proposed system is suitable to monitor and control waste in cities.

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