This paper explores the integration of smart biosensors, the Internet of Things (IoT), and machine learning for enhanced environmental monitoring. Traditional environmental monitoring methods often face challenges related to data accuracy, real-time analysis, and scalability. Smart biosensors offer advanced detection capabilities, IoT facilitates seamless data transmission, and machine learning enables sophisticated data analysis. This paper reviews the current state of these technologies, discusses their synergistic applications in air, water, soil, and ecosystem monitoring, and identifies key challenges such as technical limitations, privacy concerns, and cost factors. Future directions in sensor technology, machine learning advancements, and IoT developments are also explored, emphasizing the transformative potential of these technologies in achieving more efficient and comprehensive environmental monitoring.