# Energy-Efficient Industrial Internet of Things in Green 6G Networks
## 1 Introduction  
### The Background of the Study  
Green artificial-intelligence-based renewable energy technologies (e.g., solar and geothermal energy, together with biomass, wind, and hydroelectric power) [1, 2, 3] shape clean circular economy practices [4, 5] in the Internet of Robotic and Manufacturing Things and in cyber-physical production systems, together with Internet of Things (IoT)-sensing-network-based and deep-learning-assisted smart process planning and management [6], geospatial simulation tools, and environment mapping algorithms. Energy-harvesting technology and spectrum sensing [7, 8] across cognitive-radio-based IoT networks [9] optimize resource allocation and data fusion [10] in vehicular networks [11] and unmanned aerial vehicles [10]. Energy-efficient techniques are pivotal in IoT-device- and fog-node-based storage and computation services [12] throughout 6G networks. Computation tasks can be carried out by use of fog and edge devices while optimizing energy efficiency, resource utilization, and power consumption. Autonomous connected vehicles and smart automated machines can leverage fog-computing-based 6G IoT network energy efficient techniques supportingpervasive connectivity in extended reality environments. Physical energy, software-based power networks, and distributing renewable resources [13] configure Internet of Energy cyber-physical systems by packaged power management tools. Data processing and intelligent measurement infrastructure, energy transmission lines, software network nodes, actual-time communicating technologies, power transmission and grids, and control systems develop on smart meters, distributed energy sources, and sensors. Flexible energy control, distributed network intelligence, and optimum power current can improve energy efficiency. System power effectiveness, reliability, and stability can be attained across energy consumption and production, data processing energy management and reduction, and supply distributed equipment by wireless communication technologies. Energy sustainable networks can integrate energy aware resource and communicating node control in battery-powered connected devices and mobile terminals [14] across 6G green networks, reducing power consumption. Sixth-generation networks develop on green communication capabilities, efficient power control and signal processing, and energy-aware resource management algorithms. Sustainable green 6G IoT networks can cut down power consumption and energy overhead, while increasing coverage by intelligent communication capabilities. High throughput and energy efficiency, low latency, and intelligent traffic control, system transmission and distribution, and electricity generation [15] leverage 6G wireless network system connectivity of IoT device technologies in large-scale industrial production. Sixth-generation IoT communication and energy efficient and aware network systems can harness virtualization and mobile edge computing technologies in IoT wireless network scalability concerning operations and services. Performance is optimized by integrating spectrum sensing algorithms, sensor network fault detection, data transmission scheduling, and energy harvesting mechanisms. Industrial 6G edge computing and distributed artificial intelligence technologies [16] can be leveraged for energy consumption reduction and sensor node clustering in automated equipment operations across multi-agent system-based industrial wireless sensor networks. Propagation neural and convolutional neural networks, data-mining-based clustering and collaborative perception technologies, and machine learning algorithms can configure mutual cluster correlation in individual node resource allocation for energy efficiency optimization and industrial 6G machine and equipment networking and automated operation for production efficiency based on network sensor node energy data and cooperative spectrum sensing.