# The Impact of 6G-IoT Technologies on the Development of Agriculture 5.0: A Review
## 3 6G-IoT: New Technologies and Emerging Services
### Quantum Sensing, Communication, and Computation  
Quantum technology has been proposed for future networks as a promising technology capable of delivering super-high data transmission rates and significantly enhanced security [13; 54]. The fundamental concepts of quantum mechanics are based on the superposition principle, which asserts that until a quantum system is measured, it can exist in multiple states simultaneously. Consequently, the quantum supercomputers of the future will not process information bits but rather quantum bits (i.e., qubits) that can be in a coherent superposition of both one and zero states. Quantum technology, which includes quantum sensing, quantum communication, and quantum computation, is expected to have a substantial impact on the design of future networked computing systems [16].  
Many elementary quantum systems, including atomic spin systems, NV (nitrogen-vacancy) center ensembles, and trapped ions, can serve as quantum sensors [71]. Due to the extreme sensitivity of quantum states to even the smallest changes, these sensors have a higher sensitivity than conventional sensors, and they have the potential for more precise monitoring of physical parameters such as electromagnetic fields and temperature.  
Moreover, quantum communication is expected to revolutionize data transmission by utilizing the principles of quantum mechanics to ensure a secure and tamper-proof exchange of information. Quantum communication protocols have the ability to detect any interception or eavesdropping attempts, as the act of measuring quantum states disrupts their delicate properties. Furthermore, the implementation of quantum key distribution(QKD), a method that leverages quantum mechanics for securely creating and exchanging encryption keys between two parties, will further enhance the protection of sensitive agricultural data. Consequently, valuable data, including crop yields, market predictions, and sensor-derived information from the field, will be safeguarded, ensuring their integrity, confidentiality, and authenticity while mitigating the risks associated with unauthorized access and manipulation [72; 73]. In addition to its applications in computer communication and high-precision sensing, the academic community has shown interest in quantum computing. The main advantage of quantum computing is quantum parallelism, which enables quantum computers to simultaneously compute multiple outputs of a function, exceeding the capabilities of classical computing. Quantum computing is anticipated to be widely utilized for accelerating the analysis of big data sets and minimizing the training phase of Machine Learning (ML) algorithms. By going beyond classical binary computing, quantum computing can significantly reduce the training and execution times of machine learning algorithms, making them suitable for real-time, computationally demanding applications. The new field of research that emerges from the combination of quantum computing with machine learning is referred to as Quantum Machine Learning (QML) [74; 75].