Short Communication - (2025) Volume 14, Issue 6
Received: 01-Nov-2025, Manuscript No. sndc-26-179840;
Editor assigned: 03-Nov-2025, Pre QC No. P-179840;
Reviewed: 17-Nov-2025, QC No. Q-179840;
Revised: 24-Nov-2025, Manuscript No. R-179840;
Published:
29-Nov-2025
, DOI: 10.37421/2090-4886.2025.14.366
Citation: Chen, Emily. ”Green Communication for Smart Sensor Systems.” Int J Sens Netw Data Commun 14 (2025):366.
Copyright: © 2025 Chen E. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
The escalating demand for interconnected devices within the Internet of Things (IoT) necessitates a parallel evolution in communication strategies to ensure sustainability and efficiency. This pursuit has led to the emergence of 'green communication' as a critical area of research and development, focusing on minimizing the environmental impact of wireless networks. Specifically, smart sensor systems, which form the backbone of many IoT applications, are at the forefront of this green revolution, requiring optimized resource utilization and energy efficiency to operate effectively and minimize their ecological footprint. The advancements in low-power sensor designs, coupled with innovative energy harvesting techniques and intelligent routing protocols, are paramount to achieving these goals by reducing overall network energy consumption, thereby enabling more sustainable IoT deployments through smarter, less power-hungry communication strategies within sensor networks [1].
The inherent link between the evolution of smart sensor networks and their ability to communicate efficiently and sustainably underscores the importance of the 'green' aspect in every stage of their lifecycle. This includes sensor deployment, data transmission, and overall management, highlighting the need for innovations in energy-aware protocols, efficient spectrum sharing mechanisms, and cooperative communication strategies. By integrating these elements, the environmental footprint of these interconnected systems can be significantly reduced, paving the way for more eco-conscious technological advancement [2].
Addressing the practical challenges of implementing green communication in large-scale smart sensor systems is a significant undertaking. The development of frameworks for optimizing energy efficiency through dynamic resource allocation and intelligent sleep scheduling is crucial. These adaptive strategies, which allow communication parameters to adjust based on real-time network conditions, have demonstrated substantial power savings, leading to extended sensor lifetimes and reduced operational costs, a key consideration for widespread adoption [3].
The pervasive trend towards distributed and increasingly intelligent sensing environments demands communication paradigms that are not only low-power but also remarkably robust. Recent developments in physical layer techniques for green communication, such as spectrum sensing, adaptive modulation, and refined power control, are being actively applied to sensor networks. These techniques are instrumental in reducing interference and minimizing energy consumption, thereby enhancing the overall efficiency and viability of these networks [4].
The core functionality of smart sensor systems is increasingly dependent on efficient data aggregation and communication to fulfill their intended purposes. Novel approaches to green data collection and transmission are being explored, with a particular focus on minimizing the energy expenditure of mobile sensors. Techniques such as opportunistic communication and the strategic use of cooperative relays hold significant promise for enhancing energy efficiency within dynamic and often unpredictable sensor network environments [5].
The integration of artificial intelligence (AI) into smart sensor systems presents a transformative opportunity for advancing green communication. AI-powered predictive algorithms are being investigated for their potential to optimize communication schedules, reduce redundant data transmissions, and enable proactive energy management strategies. The ultimate goal is the creation of more intelligent and inherently energy-conscious sensor network operations, a significant leap forward in sustainable technology [6].
The impact of various wireless technologies on the energy efficiency of smart sensor networks is a critical area of study. Comparative analyses of different communication protocols, including widely adopted ones like LoRaWAN and NB-IoT, from a green communication perspective, offer valuable insights. This kind of analysis is essential for guiding the selection of the most energy-efficient solutions tailored to the specific requirements of diverse sensor network applications [7].
Energy harvesting is emerging as a pivotal technology for enabling truly green smart sensor systems, significantly reducing their reliance on conventional power sources. A review of state-of-the-art energy harvesting technologies and their seamless integration with wireless sensor networks highlights their capability to power sensors and communication modules. This approach not only reduces the need for batteries but also minimizes the overall maintenance demands of these distributed systems [8].
The principles of green communication are being meticulously extended to the physical layer of smart sensor networks, introducing innovative techniques to improve performance while reducing energy usage. The exploration of advanced concepts like distributed MIMO and cooperative communications aims to enhance spectral efficiency and significantly lower transmission power. This focus on the physical layer is crucial for achieving superior network performance with a substantially reduced energy footprint [9].
The development of energy-efficient routing protocols is a fundamental aspect of supporting green communication within smart sensor networks. The introduction of novel adaptive routing algorithms, which judiciously consider factors like residual energy and link quality for path selection, is a key advancement. Such approaches are designed to prolong the overall network lifetime and minimize energy waste during essential data forwarding operations, contributing to a more sustainable network infrastructure [10].
The intersection of green communication and smart sensor systems is a rapidly evolving field, driven by the imperative for optimized resource utilization and energy efficiency in burgeoning IoT deployments. Advancements in low-power sensor designs, energy harvesting techniques, and intelligent routing protocols are crucial for minimizing network energy consumption. These strategies collectively enable sustainable IoT initiatives by fostering smarter, less power-demanding communication within sensor networks [1].
The evolution of smart sensor networks is intrinsically tied to their capacity for efficient and sustainable communication. The 'green' aspect profoundly influences sensor deployment, data transmission, and management. Innovations in energy-aware protocols, spectrum sharing, and cooperative communication strategies are actively being pursued to diminish the environmental footprint of these interconnected systems [2].
Implementing green communication in large-scale smart sensor systems presents practical challenges that require dedicated solutions. Frameworks for optimizing energy efficiency through dynamic resource allocation and intelligent sleep scheduling are being developed. Adapting communication parameters based on real-time network conditions has shown significant power savings, thereby extending sensor lifetime and reducing operational costs [3].
The increasing trend towards distributed and intelligent sensing necessitates communication paradigms that are both low-power and robust. Recent developments in physical layer techniques for green communication, including spectrum sensing, adaptive modulation, and power control, are being applied to sensor networks. These methods are vital for reducing interference and overall energy consumption [4].
Smart sensor systems increasingly rely on efficient data aggregation and communication to achieve their objectives. This has spurred the exploration of novel approaches for green data collection and transmission, focusing on minimizing the energy expenditure of mobile sensors. Techniques such as opportunistic communication and cooperative relays are being evaluated for their potential to improve energy efficiency in dynamic sensor network environments [5].
The integration of artificial intelligence (AI) into smart sensor systems opens new avenues for green communication. AI-powered predictive algorithms are being investigated for their ability to optimize communication schedules, reduce redundant data transmission, and enable proactive energy management. The aim is to foster more intelligent and energy-conscious sensor network operations [6].
The impact of various wireless technologies on the energy efficiency of smart sensor networks is being examined. Comparative studies of different communication protocols, such as LoRaWAN and NB-IoT, from a green communication standpoint, provide valuable insights. This analysis aids in selecting the most energy-efficient solutions for specific sensor network applications [7].
Energy harvesting is a critical enabler of truly green smart sensor systems. A review of state-of-the-art energy harvesting technologies and their integration with wireless sensor networks highlights their role in powering sensors and communication modules. This reduces reliance on batteries and minimizes maintenance needs [8].
Green communication principles are being extended to the physical layer of smart sensor networks. Techniques like distributed MIMO and cooperative communications are being explored to enhance spectral efficiency and reduce transmission power, aiming for improved network performance with lower energy consumption [9].
The development of energy-efficient routing protocols is fundamental to supporting green communication in smart sensor networks. Novel adaptive routing algorithms that consider residual energy and link quality for path selection are being introduced. These approaches aim to prolong network lifetime and minimize energy waste in data forwarding [10].
This collection of research explores the multifaceted field of green communication within smart sensor systems. Key areas of focus include optimizing resource utilization and energy efficiency through low-power sensor designs, energy harvesting, and intelligent routing protocols. The research highlights the importance of sustainable communication strategies for IoT deployments, emphasizing energy-aware protocols, spectrum sharing, and cooperative communication to reduce environmental impact. Practical implementation challenges are addressed through dynamic resource allocation and intelligent sleep scheduling. Advancements in physical layer techniques, AI-enabled optimization, and comparative analyses of wireless technologies are contributing to more efficient and robust sensor networks. The development of energy-efficient routing protocols and the integration of energy harvesting technologies are crucial for prolonging network lifetime and minimizing energy waste, ultimately driving towards more sustainable and energy-conscious sensor network operations.
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