# Energy-Efficient Industrial Internet of Things in Green 6G Networks
## 10 Conclusions  
Sixth-generation-network-based energy efficient systems integrate energy harvesting and efficient computing techniques, fog and edge device computation resources, and low power communications [12] through sensing and localization accuracy, data sharing devices, and connectivity and computing capabilities optimization. Sixth-generation communications can deploy fog nodes to facilitate ubiquitous connectivity and attain low latency. Energy-efficient 6G IoT fog computing technologies shape task offloading, latency reduction, and resource allocation. Energy-efficient environmentally aware wireless communication technologies and 6G sensor-based IoT networks [28] can reduce carbon emissions. IoT devices can gather accurate and detailed smart sensory data, and unmanned aerial vehicles serve as edge computing nodes for input processing, analysis, and aggregation, resulting in IoT energy efficiency and power optimization. Green IoT and cloud-based computing technologies can be deployed in aerial imagery and monitoring, being instrumental in transmission energy efficiency and connection accuracy through efficient IoT data collection and transmission. Edge-intelligence-based high-reliability real-time service delivery can decrease energy consumption by autonomous trajectory design and planning techniques and smart solar-powered sensor nodes. Wireless power transfer and coordinated charging scheduling technologies can enhance vehicular mobility and dynamic traffic-based collaborative energy management [29] across green 6G IoV infrastructures. Software-defined networking distributed edge computing nodes can gather traffic data and enable vehicle-to-everything communication by green IoV systems, Non-orthogonal Multiple Access (NOMA) technologies and 6G-enabled vehicular networks, while increasing spectrum efficiency and connectivity. Energy-efficient collaboration and resource allocation develop on multi-radio access technologies and on vehicular communication mechanisms in dynamic traffic environments and across green IoV and distributed vehicle-to-everything networks. Energy-efficient resource allocation can improve green vehicle-to-everything communication and vehicular network routing performance by integrating real-time traffic data and varying vehicle connectivity computation resources. This leads to reduced dynamic transmission and communication energy consumption across IoV infrastructures.  
Contextual awareness-based adaptive intelligence 6G technologies can optimize wireless connectivity and efficient resource utilization. Adaptive machine-learning-based transceiver chains can enhance the signal-to-noise ratio, furthering broader coverage and 6G network performance and efficiency for fault-resilient network operation across integrated industrial IoT autonomous robotic environments by extended reality and metaverse technologies. Adaptable code rate designs assist 6G wireless communications, cutting down signal distortions by digital twin extended reality and sensor fusion technologies. Generative AI and extended reality-based 6G device adaptive capabilities can optimize resource allocation and predict network performance by generative AI 6G digital twin integrated sensing and communication technologies.