The Evolution of Wireless Sensor Networks through Smart Radios for Energy Efficiency

. This article investigates the significant influence of smart radios on the energy efficiency of Wireless Sensor Networks (WSNs). It explores the incorporation of intelligent radios as a crucial element to enhance WSNs’ sustainability, providing a novel approach to tackle energy-related challenges. Smart radios are essential for prolonging the lifespan of sensor devices and reducing the environmental effect of WSNs by autonomously adjusting communication protocols and optimizing energy consumption. This paper also highlights the differences between 5G and 6G technologies within the WSNs framework. While 5G brought improvements in data speed and connectivity, 6G represents a significant progress by prioritizing energy efficiency as a fundamental goal. This shift represents a fundamental change, with a primary focus on achieving extremely low energy consumption and ensuring the sustainable operation of WSNs. The paper examines crucial technological factors enabling 6G to outperform its predecessor, establishing it as a revolutionary force in the field of wireless communication for sensor networks. This research illuminates the crucial function performed by smart radios in connecting the desire for energy efficiency with the changing environment of wireless sensor networks.


Introduction
Smart radios are changing the game in the fast-paced world of wireless communication and paving the way for more sustainable energy practices in WSNs.Conversations about 5G and the next-gen network, 6G, have recently taken center stage, with many highlighting the role of AI in this technological shift [1,2].Today, wireless sensor networks link a plethora of devices that need to communicate with each other in order to function, and they are ubiquitous in many fields, including environmental monitoring and industrial automation.Nevertheless, there are substantial obstacles associated with the proliferation of these networks, the most pressing of which is the requirement for environmentally friendly energy sources to supply electricity to the numerous devices housed within.The integration of intelligence into communication systems is what smart radios, an integral part of the upcoming wireless network generation, claim can solve these problems.In contrast to more conventional forms of communication, smart radios can change their settings in response to environmental factors, traffic patterns, and energy availability.This flexibility is essential for sustainable energy usage and for optimizing network efficiency.Smart radios are reshaping the communication landscape by incorporating artificial intelligence (AI) algorithms and cognitive capabilities.In order to make educated judgments regarding channel access, transmission power, and data routing, smart radios use sophisticated sensing mechanisms in conjunction with machine learning algorithms.Devices in the wireless sensor network have a longer operating lifespan thanks to this smart method that reduces energy waste.Compared to 5G, 6G is a huge improvement in data throughput, latency, and connection, not to mention an incremental update.The transition from 5G to 6G highlights the significance of incorporating sustainable practices, with smart radios being an essential facilitator.The globe is already seeing the massive rollout of 5G networks, but preparations for 6G, the next generation of wireless communication, are already under way.A quantum leap in data speeds, latency, and connection is signified by the move from 5G to 6G, which is more than just an incremental update [3].Concerns regarding the energy footprint of wireless infrastructure were voiced throughout the 5G era, which brought about unparalleled data rates and connection.Sustainability must be a cornerstone of 6G, according to an increasing number of experts.To ensure that technological progress and environmental responsibility go hand in hand, AI-enabled smart radios connect the dots between the present and the future of wireless communication, specifically the 6G networks.The effort to incorporate sustainability into wireless communication networks relies heavily on artificial intelligence.Smart radios automatically optimize network operations by drawing on AI, striking a balance between improving performance and conserving energy.By optimizing resource allocation, predicting network demand, and enabling proactive energy management, AI-driven predictive analytics add to the sustainability story.

Literature review
The combination of intelligent radios and environmentally responsible energy practices in wireless sensor networks (WSNs) is a paradigm shift that solves the issues that are associated with contemporary wireless communication technology.The purpose of this literature review is to investigate the development of wireless networks, the advent of smart radios, and the essential role that artificial intelligence (AI) plays in the promotion of sustainability.Throughout the course of the conversation, we will traverse the realms of 5G and the predicted 6G, bringing to light the interconnectivity of technical progress, intelligence, and ecological responsibility.[4] In recent years, wireless sensor networks have emerged as an indispensable component in a wide range of applications, including automated manufacturing, environmental monitoring, and healthcare.Figure 1, as presented by Alkhayyat et al. [5], illustrates the diverse stages of wireless sensor body networks designed for next-generation health applications.On the other hand, the extensive deployment of these networks has resulted in considerable issues regarding energy.Traditional communication technologies frequently suffer from energy inefficiency, which leads to increased operational expenses and an impact on the environment.For this reason, it is absolutely necessary to look for ways to implement sustainable energy solutions in WSNs.Intelligent radios, which are a fundamental component of the next generation of wireless networks, are designed to include intelligence and adaptability into their architecture.Smart radios, in contrast to conventional radios, are able to dynamically alter their parameters using real-time conditions, which allows them to optimize both the performance of the network and the amount of energy that is consumed.Through the incorporation of artificial intelligence algorithms into smart radios, these devices are equipped with sophisticated sensing mechanisms and the capacity to learn through machine learning [6,7].This enables the radios to make decisions independently about channel access, transmission power, and data routing.The combination of artificial intelligence and smart radios brings about a degree of adaptability that is essential for achieving sustainability.Machine learning algorithms are constantly learning from the dynamics of the network, and they make judgments based on this information in order to minimize energy consumption without affecting connectivity.Through the forecasting of network demand, the facilitation of proactive energy management, and the optimization of resource allocation, predictive analytics empowered by artificial intelligence further improve sustainability.The versatility of this system guarantees that energy is used effectively, which is in line with the objective of developing wireless networks that are environmentally friendly.In terms of the progression of wireless communication, the shift from 5G to 6G constitutes a huge leap forward.Additionally, questions have been expressed regarding the energy footprint of wireless infrastructure as a result of the introduction of 5G, which has brought about unparalleled data rates and connection.[15] There is a growing understanding that sustainability must be at the forefront of technical breakthroughs, and this is occurring at the same time that the world is anticipating the introduction of 6G services.The versatility of smart radios, which is driven by artificial intelligence, helps bridge the gap between the wireless communication technologies that are currently in use and the future that is envisioned for 6G networks [1].It is impossible to overestimate the significance of artificial intelligence in the process of developing environmentally friendly wireless communication.[16] The application of artificial intelligence acts as the cornerstone, enabling smart radios to optimize network operations on their own.The implementation of this clever method not only improves performance but also helps to reduce energy consumption.A feedback loop of continuous improvement is created by the combination of the proactive decision-making skills of artificial intelligence (AI) and machine learning.This feedback loop makes wireless sensor networks more durable and sustainable.Despite the fact that the combination of artificial intelligence and smart radios presents promising options for sustainability, obstacles still exist.In order to successfully implement intelligent systems, it is necessary to give careful consideration to the implications of security, privacy, and ethics.Important features of smart radio implementation include limiting the amount of energy that artificial intelligence algorithms consume and ensuring that the system is robust against attacks from adversaries.Standardization and interoperability are further issues that need to be solved in order to accomplish the goal of facilitating the smooth integration of smart radios into both existing wireless networks and future wireless networks.This study explores the intricacies of linking wireless sensor networks to the Internet for the purpose of controlling electrical devices.
There is an absence of a thorough analysis of the social, psychological, and health challenges associated with 6G.
[13] 2022 A perspective on time toward wireless 6G Addressing issues related to consensus and distributed learning, this article primarily focuses on the wireless access aspect, exhibiting a bias in the discussion.
Most sensor nodes in wireless sensor networks (WSNs) function within energy constraints, significantly influencing the system's overall efficiency, reliability, and lifespan.
For the purpose of demonstrating the practical influence that smart radios have on sustainability in wireless sensor networks, several case studies and real-world implementations have been presented, as shown in table 1.These studies show the advantages in efficiency, energy savings, and increased network performance that may be obtained through the implementation of intelligent and adaptive radio systems.The versatility and S E3S Web of Conferences 477, 00072 (2024) https://doi.org/10.1051/e3sconf/202447700072STAR'2023 promise of smart radios in a variety of settings is demonstrated by the fact that their applications in the real world span a wide range of industries, such as smart cities, agriculture, and healthcare.

Methodology
The methodology provided in this paper is to investigate and apply smart radios as a transformative solution to achieve sustainable energy practices in wireless sensor networks (WSNs).Our approach aims to modernize wireless communication technologies for a more environmentally responsible future by exploring the relationship between 5G and impending 6G networks and highlighting the important role of artificial intelligence (AI).[17] The primary issue tackled in this methodology is the requirement for sustainable energy practices in wireless sensor networks.The growing utilization of Wireless Sensor Networks (WSNs) in diverse applications has raised considerable concerns about the energy inefficiencies of conventional communication methods.The shift from 5G to 6G networks presents a favorable opportunity to incorporate intelligent radios and utilize artificial intelligence to accomplish sustainability objectives.In order to tackle the current issue, we suggest a mathematical model that encompasses the crucial factors that impact the energy efficiency of intelligent radios in wireless sensor networks (WSNs).

Energy Consumption Model
The overall energy consumption (Etotal) of a smart radio can be represented by a mathematical function that takes into account the transmission power (Ptx), channel access rate (), and the duration of channel access attempts (t).
The equation (1) represents the core correlation between the energy expended during transmission, the rate at which the channel is accessed, and the length of each attempt to access it.

A Smart Radio Adaptation Algorithm
An adaptive algorithm is a type of algorithm that governs the behavior of smart radios in order to dynamically modify their parameters based on the situations that are occurring in real time.Within the framework of a reinforcement learning technique, the adaption algorithm can be written as follows:

Integration of AI for Predictive Energy Management in 5G and the Anticipated 6G Networks
With the transition from 5G to the upcoming 6G networks, the use of artificial intelligence (AI) in improving the flexibility and decision-making powers of smart radios becomes more crucial [18].The incorporation of artificial intelligence, specifically through the implementation of predictive energy management, signifies a fundamental change in how we approach the issues of energy efficiency and sustainability in wireless sensor networks.This talk will explore the intricacies of incorporating AI into wireless communication technologies.It will compare and contrast the features of 5G and 6G and emphasize the profound impact of AI in determining the future of these technologies [1].

Improving Flexibility with Anticipatory Energy Management
In both 5G and the forthcoming 6G networks, the capacity of intelligent radios to adapt is essential for optimizing energy usage and guaranteeing effective network performance.The adaptation process heavily relies on AI-driven predictive energy management.Smart radios utilize machine learning algorithms to predict fluctuations in network demand, device power needs, and possible energy deficits by utilizing past data.Smart radios are able to use their predictive capability to proactively modify their parameters, thus ensuring optimal performance in environments that are always changing.[19] The importance of AI in 5G networks lies in its ability to optimize network efficiency, allocate resources effectively, and improve user experience.Predictive analytics models in 5G networks primarily concentrate on predicting data traffic patterns and enhancing resource allocation efficiency.AI algorithms have the capability to forecast the times when usage is at its highest, enabling the allocation of spectrum in a flexible manner to cater to the changing needs of users.Although 5G networks do benefit from AI-driven optimizations, the primary focus is on enhancing data throughput and developing user-centric services, rather than explicitly prioritizing energy management.

Advancing to the 6G era: Emphasizing sustainability and achieving ultralow latency
The upcoming 6G networks mark the beginning of a new age characterized by a strong focus on sustainability and extremely low latency.With the increasing growth of the Internet of Things (IoT) and the emergence of applications that require low latency, the importance of AI in predictive energy management becomes even more crucial.6G aims to create a network that is both faster and more sustainable than its predecessor.It will achieve this by using smart radios that not only prioritize performance but also prioritize energy conservation.[20]

Predictive Energy Management in 6G
In the context of 6G, the utilization of artificial intelligence (AI) for predictive energy management extends beyond the mere optimization of data flow and resource allocation.The scope includes the prediction of device-specific energy demands and the anticipation of future energy deficits within the network.Machine learning models examine past data, considering device attributes, environmental circumstances, and network fluctuations.The comprehensive methodology enables intelligent radios in 6G networks to proactively make decisions, such as optimizing transmission power, choosing energy-efficient routes, and dynamically managing resources to maintain continuous network functionality.[ The role of artificial intelligence (AI) in shaping the future of wireless communication is undergoing a significant transformation with the move from 5G to 6G. 6G enhances the concept of network intelligence established by 5G by firmly integrating AI into the network infrastructure to tackle sustainability concerns.Smart radios, coupled with sophisticated machine learning algorithms, function as proactive entities that not only react to current network conditions but also predict future needs.This evolution is consistent with the overarching objectives of establishing robust, effective, and environmentally friendly wireless communication systems.

The Convergence of AI, Environmental Sustainability & Minimal Delay
Within the transition from 5G to 6G, the convergence of artificial intelligence, sustainability, and extremely low latency arises as a distinctive characteristic.AI-driven predictive energy management is in line with the sustainability objectives of 6G networks.Anticipating and addressing possible energy shortages enhances the overall effectiveness and durability of the network.In addition, the ultra-low latency demands of 6G are met not only through accelerated data transfer, but also through proactive decision-making, guaranteeing that crucial communications take place with minimal delay.

Analysis and Discussion
Wireless sensor networks (WSNs) are increasingly being deployed for environmental, medical, and industrial monitoring applications.As wireless communication becomes more complex, integrating smart radios becomes an innovative way to achieve sustainable energy practices in wireless sensor networks (WSNs).In the context of wireless sensor networks, we examine the main features of smart radios in this analysis and discussion, including their effects on energy efficiency, adaptability, and wider sustainability implications.Energy Efficiency and Smart Radios: Improving energy efficiency is one of smart radios' main contributions to WSNs.Conventional wireless communication systems frequently have inefficient power consumption, which reduces the lifespan of the device and raises operating expenses.[22] Artificial intelligence (AI) and adaptive algorithms enable smart radios to dynamically modify their parameters in response to current circumstances.When it comes to energy consumption, this flexibility is revolutionary since it enables smart radios to maximize efficiency and reduce needless power use.As a result, the WSN is able to operate for longer periods of time and with greater energy efficiency.Adaptive Algorithms and Real-time Adjustments: One of the key features of smart radios is their adaptive algorithms, which enable real-time changes.These adaptive algorithms allow radios to react dynamically to changes in the environment, network demand, and device characteristics, in contrast to static communication protocols.This flexibility is essential in situations where demand, interference, or energy supply changes and affects the wireless network.Smart radios can maximize channel access, transmission power, and data routing through AI-driven decision-making, guaranteeing that energy resources are used effectively.[23] Implications for Sustainability: The revolution in smart radios has significant implications for sustainability.The environnemental impact of Wireless communication technologies is being examined as WSNs become more and more important in a variety of applications.Conventional networks have a large carbon footprint because of their static and energyinefficient protocols.Smart radios open the door to more environmentally friendly behaviors with their flexibility and intelligent energy management.Broader sustainability objectives are aligned with the decentralized control architecture, which is frequently linked to smart radios in the envisioned 6G networks.Edge computing further contributes to energy savings S E3S Web of Conferences 477, 00072 (2024) https://doi.org/10.1051/e3sconf/202447700072STAR'2023 by reducing the need for centralized data centers by dispersing computational processes closer to the data source.The progression of technology from 5G to 6G: The examination of smart radios in the framework of wireless sensor networks illustrates the continuous advancement of technology from 5G to 6G.Higher data speeds and reduced latency were brought about by 5G; however, 6G broadens the focus to include sustainability, ultra-low latency, and intelligent decisionmaking.In 6G, AI plays a more significant role as smart radios move from being reactive to proactive entities.With 6G, edge computing is prioritized in response to the increasing demand for localized data processing, which lowers latency and improves energy efficiency.This evolution represents a move away from just satisfying data throughput requirements to building an intelligent, sustainable, and future-proof wireless communication ecosystem.

Energy Efficiency and Adaptability
The advancement of intelligent radios in wireless sensor networks (WSNs) signifies a significant improvement in energy efficiency when compared to the current level of technology.Conventional wireless communication methods frequently encounter difficulties with fixed protocols that result in inefficient energy usage.Smart radios, which are equipped with adaptive algorithms and artificial intelligence (AI), exhibit exceptional adaptability in comparison.They adaptively modify parameters instantaneously, in accordance with variations in the surroundings, network requirements, and device attributes.The versatility of this system is in sharp contrast to conventional communication systems, which are limited in efficiency benefits by rigid protocols.The current level of technological advancement is frequently defined by fixed and pre-established methods of communication, which presents difficulties in meeting the ever-changing and varied requirements of modern Wireless Sensor Networks (WSNs).

Predictive Energy Management and Sustainability
The incorporation of AI-powered predictive energy management into smart radios is a notable deviation from the current standard.Smart radios utilize proactive tactics to anticipate network demand, device energy needs, and potential energy deficiencies, in contrast to conventional systems that depend on reactive approaches.This ability to anticipate future events allows for proactive modifications, so minimizing energy exhaustion and contributing to the continuous operation of the network.This ability to foresee corresponds with wider environmental objectives and indicates a shift away from the reactive methods of energy management now in use.During the shift from 5G to the expected 6G networks, this divergence becomes even more evident.6G networks, driven by a sustainability-focused strategy, aim to implement a comprehensive predictive energy management system that goes beyond optimizing data traffic.This system includes projecting the energy consumption of individual devices and making intelligent decisions based on that information.

Technological Evolution from 5G to 6G
One significant difference between smart radios and the current technology is the continuous technological advancement from 5G to the expected 6G networks.Although 5G networks brought about faster data speeds and reduced delay, the emergence of intelligent radios in 6G networks intensifies the emphasis on sustainability, extremely low latency, and intelligent decision-making.The latest technology frequently faces challenges in keeping up with these ever-changing demands.In 6G, the significance of AI increases as smart radios evolves from being adaptive entities to becoming proactive decision-makers.The focus on edge computing in 6G is in line with the increasing demand for localized data processing, which aims to decrease latency and enhance energy efficiency.The advancement of technology indicates a transition from just meeting the requirements for transmitting data to establishing a wireless communication system that is intelligent, sustainable, and able to accommodate new technologies.[24] 6 Challenges and Future Directions Although there have been promising improvements, there are still obstacles that need to be overcome in order to fully utilize the capabilities of smart radios in wireless sensor networks (WSNs).In order to achieve a smooth integration of smart radios into current and upcoming networks, it is crucial to tackle technical obstacles such as interoperability, security, and standardization.The development of smart radio technology is significantly influenced by economic and regulatory factors.Furthermore, it is imperative to consistently evaluate and alleviate environmental consequences to guarantee that the advantages of energy efficiency are not achieved at the expense of ecological sustainability.[25] Regarding future prospects, progress in electric vehicle (EV) and battery technologies are expected to have a significant influence on the energy framework of WSNs.Exploring the integration of electric vehicles (EVs) with bidirectional energy flow, often known as vehicleto-home (V2H) technologies, offers an attractive opportunity for further investigation.The implementation of standardized protocols and interoperability will be crucial in fully harnessing the capabilities of smart radios in many applications.

Conclusion
The suggested methodology combines mathematical modelling, adaptive algorithms, and AI-driven predictive analytics to transform wireless sensor networks.This technique provides a complete approach to attaining sustainable energy practices in next-generation wireless communication technologies by examining the transition from 5G to 6G networks and highlighting the importance of smart radios and artificial intelligence.The contrast between smart radios and the latest advancements in wireless sensor networks emphasizes a significant shift towards improved energy efficiency, sustainability, and intelligent decision-making.The versatility of intelligent radios, powered by artificial intelligence, distinguishes them from traditional systems, enabling immediate modifications and optimal utilization of energy.Smart radios are further differentiated by their predictive energy management capabilities, which enhance the ongoing functionality of the network and align with wider sustainability objectives.The continuous technological advancement from 5G to 6G solidifies smart radios as the leaders of the upcoming generation, ensuring a wireless communication environment that is not only quicker but also more intelligent and environmentally friendly.Despite the challenges faced by current advanced technology in dealing with fixed procedures and responsive energy control, intelligent radios serve as a clear example of the ongoing progress that is shaping the future of wireless communication technologies.

Fig. 1 .
Fig. 1.Wireless sensor networks for healthcare applications based on the Internet of Things (IoT)

Table 1 .
Literature Review Comparison with Previous work.
[10]2019 Advances and Opportunities in Passive Wake-Up Radios with Wireless Energy Harvesting for the Internet of Things Applications.Provides a comprehensive examination of AI applications within WSNs, yet does not specifically explore the progress in smart radios for sustainable energy.