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<h2>Introduction</h2>
<p>The rapid expansion of the Internet of Things (IoT) paradigm has led to the deployment of sensor nodes across a diverse range of applications, from smart cities and industrial automation to environmental monitoring and precision agriculture (Ayaz et al., 2019; Farooq et al., 2019; Lezoche et al., 2020; Hashem et al., 2016). A critical challenge, particularly for IoT deployments in remote or inaccessible environments, is the provision of a reliable and sustainable power supply. Traditional battery-powered solutions suffer from finite energy capacity, necessitating periodic replacement or recharging, which can be logistically complex, costly, and environmentally detrimental in large-scale or geographically dispersed sensor networks (Elahi et al., 2020; Erdem & Gungor, 2018; Kiruba & Benita, 2021).</p><p>Remote environments, characterized by harsh conditions, lack of infrastructure, and infrequent human access, amplify these power constraints. For instance, monitoring agricultural fields, remote wilderness areas, or critical infrastructure like transmission lines requires sensor nodes to operate autonomously for extended periods without human intervention (Ali, 2021; Shi & Wang, 2020; Tan & Panda, 2011). The vision of ubiquitous, self-powered IoT necessitates a paradigm shift from conventional power sources to innovative energy solutions that can harness ambient energy present in the deployment environment (Elahi et al., 2020).</p><p>Energy harvesting (EH) technologies offer a promising avenue for powering IoT sensor nodes by converting ambient energy into usable electrical power. Common ambient sources include solar radiation, thermal gradients, mechanical vibrations, and radio frequency (RF) signals (Elahi et al., 2020; Sharma et al., 2018). While single-source energy harvesting has demonstrated viability in specific applications, its effectiveness is often limited by the intermittent and fluctuating nature of individual energy sources. For example, solar energy is unavailable at night or during cloudy weather, and vibrational energy may only be present during specific events (Li et al., 2020; Izadgoshasb, 2021).</p><p>To overcome these limitations and ensure continuous power availability, hybrid energy harvesting (HEH) systems have emerged as a robust solution. HEH systems combine multiple energy harvesting mechanisms to leverage the complementary nature of different ambient sources, thereby enhancing overall power output, reliability, and operational duration (Dipon et al., 2023; Kim et al., 2019; Xiao et al., 2023). By integrating two or more harvesting technologies, such as photovoltaic (PV) and thermoelectric generators (TEG), or piezoelectric and PV, HEH systems can mitigate the intermittency of individual sources and provide a more stable power supply, even under varying environmental conditions (Mishu et al., 2021; Qiu et al., 2020).</p><p>This paper aims to explore the design, implementation, and performance evaluation of hybrid energy harvesting solutions for sustainable self-powered IoT sensor nodes, specifically focusing on applications in remote environments. We delve into the synergies between different harvesting technologies and propose an optimized system architecture tailored for continuous operation. The objective is to demonstrate the feasibility and advantages of HEH in achieving long-term autonomy for remote IoT deployments, thereby reducing maintenance burdens and promoting environmental sustainability. The subsequent sections will provide a comprehensive literature review, detail the proposed methodology, present experimental results, discuss their implications, and conclude with future research directions.</p>
<h2>Literature Review</h2>
<p>The concept of self-powered wireless sensor nodes has been a significant area of research for over a decade, driven by the desire to eliminate battery reliance and extend network lifetimes (Tan & Panda, 2011; Erdem & Gungor, 2018). Initial efforts focused on single-source energy harvesting, primarily leveraging solar, thermal, or kinetic energy, depending on the application context.</p><h4>Solar Energy Harvesting</h4><p>Solar energy remains one of the most abundant and widely utilized ambient energy sources for outdoor IoT applications. Photovoltaic (PV) cells convert sunlight directly into electricity, offering high power density under optimal conditions (Sharma et al., 2018). Li et al. (2020) demonstrated the feasibility of harvesting solar energy for self-powered environmental wireless sensor nodes, highlighting its potential but also acknowledging its dependence on light intensity and diurnal cycles. However, the intermittency of solar radiation (e.g., at night, during heavy cloud cover, or in shaded areas) necessitates energy storage mechanisms, typically supercapacitors or rechargeable batteries, to ensure continuous operation (Bouřa, 2020).</p><h4>Thermal Energy Harvesting</h4><p>Thermoelectric generators (TEGs) convert temperature differences into electrical energy via the Seebeck effect. This method is particularly attractive in environments with consistent temperature gradients, such as industrial settings, automotive applications, or even human body heat (Haug, 2017; Mehne et al., 2016; Sabban, 2022). Xiao et al. (2023) investigated self-powered IoT sensor nodes harvesting hybrid indoor ambient light and heat energy, demonstrating the potential in controlled environments. While TEGs offer continuous power generation as long as a temperature gradient exists, their power output is generally lower than PV cells and highly dependent on the magnitude of the temperature difference (Haug, 2017).</p><h4>Vibration/Kinetic Energy Harvesting</h4><p>Mechanical vibrations, prevalent in many environments (e.g., bridges, machinery, human movement), can be converted into electrical energy using piezoelectric transducers or electromagnetic generators. Piezoelectric energy harvesting (PEH) is gaining traction for its ability to convert mechanical strain into electrical energy, making it suitable for applications where vibrations are frequent (Asthana & Khanna, 2021; Izadgoshasb, 2021). Li et al. (2019) explored nonlinear electromagnetic energy harvesting systems for self-powered wireless sensor nodes, showcasing its potential. Dipon et al. (2023) also reported on self-sustainable IoT-based remote sensing using stacked piezoelectric transducers. However, the efficiency of PEH is highly dependent on the frequency and amplitude of vibrations, and optimizing resonant frequencies is crucial for practical implementation.</p><h4>Radio Frequency (RF) Energy Harvesting</h4><p>RF energy harvesting, while offering the potential for ubiquitous power from ambient RF signals (e.g., Wi-Fi, cellular networks), typically provides very low power densities, limiting its application primarily to ultra-low power devices or as a supplementary source (Elahi et al., 2020). Recent advancements in 6G communication networks and intelligent reflecting surfaces might improve this in the future, but current practical applications for remote sensor nodes are still challenging (Alwis et al., 2021; Nawaz et al., 2019; Wang et al., 2023; Wu et al., 2021).</p><h4>Hybrid Energy Harvesting (HEH) Systems</h4><p>The inherent intermittency and variability of single ambient energy sources often render them insufficient for reliably powering IoT nodes over extended periods, especially in remote settings (Elahi et al., 2020). This has spurred significant research into hybrid energy harvesting (HEH) systems, which combine two or more harvesting mechanisms to achieve greater power stability and higher overall energy output. The principle behind HEH is to leverage the complementary characteristics of different energy sources; for example, when solar energy is low, thermal gradients might be high, or vibrations might be present (Kim et al., 2019).</p><p>Several combinations have been explored. PV-TEG hybrid systems are particularly common, as solar radiation often correlates with temperature differences. Mishu et al. (2021) proposed an adaptive TE-PV hybrid energy harvesting system for self-powered IoT sensor applications, demonstrating improved performance over individual sources. Qiu et al. (2020) designed a self-powered control interface with hybrid triboelectric and photovoltaics energy harvesting, suitable for smart home applications. Dipon et al. (2023) combined piezoelectric and thermoelectric generators for remote sensing, indicating the versatility of HEH. Xiao et al. (2023) investigated a hybrid system for indoor light and heat energy, showcasing its applicability beyond outdoor environments.</p><p>The design of HEH systems typically involves multiple energy transducers, a power management unit (PMU) to efficiently combine and regulate the harvested energy, and an energy storage element (e.g., battery or supercapacitor) to buffer energy fluctuations (Bouřa, 2020; Elahi et al., 2020; Xu et al., 2014). The PMU is critical for maximizing power transfer from each source, managing charging of the storage device, and providing a stable voltage output to the sensor node (Kim et al., 2019). Table 1 summarizes the characteristics of common single-source energy harvesting technologies.</p><figure class="table-figure"><table><thead><tr><th>Energy Source</th><th>Harvesting Mechanism</th><th>Typical Power Density (μW/cm²)</th><th>Advantages</th><th>Disadvantages</th><th>Applicability in Remote IoT</th></tr></thead><tbody><tr><td>Solar (PV)</td><td>Photovoltaic Effect</td><td>100-10,000</td><td>High power density, mature technology, widely available outdoors</td><td>Intermittent (night, clouds), sensitive to shading, requires direct sunlight</td><td>High, but requires energy storage for continuous operation</td></tr><tr><td>Thermal (TEG)</td><td>Seebeck Effect</td><td>1-100</td><td>Continuous power if ΔT exists, robust, no moving parts</td><td>Low power density, requires significant temperature gradient</td><td>Moderate, good for environments with stable heat sources/sinks</td></tr><tr><td>Vibration (PEH)</td><td>Piezoelectric Effect</td><td>1-1,000</td><td>High power density possible at resonance, small form factor</td><td>Intermittent, frequency-dependent, requires specific vibration sources</td><td>Moderate, useful near machinery, infrastructure, or environmental motion</td></tr><tr><td>Electromagnetic</td><td>Inductive/Capacitive</td><td>1-10,000</td><td>High power from strong fields, suitable for specific industrial uses</td><td>Requires strong, specific magnetic fields (e.g., transmission lines)</td><td>Limited, niche applications (e.g., power line monitoring) (Shi & Wang, 2020)</td></tr><tr><td>RF</td><td>Rectenna</td><td><0.1-10</td><td>Ubiquitous, low power for ultra-low power devices</td><td>Very low power density, short range for efficient harvesting</td><td>Low, primarily supplementary for remote IoT</td></tr></tbody></table><figcaption>Table 1. Comparison of Single-Source Energy Harvesting Technologies for IoT.</figcaption></figure><p>The current state of research clearly indicates a trend towards HEH as the most viable path for truly self-sustaining IoT sensor nodes, particularly in remote and challenging environments where power autonomy is paramount (Ali, 2021). However, optimizing the selection of harvesting technologies, designing efficient power management circuits, and evaluating long-term performance under diverse environmental conditions remain active areas of research.</p>
<h2>Methodology</h2>
<p>To address the challenges of sustainable power for IoT sensor nodes in remote environments, this study proposes and evaluates a hybrid energy harvesting (HEH) system architecture. The methodology encompasses the system design, component selection, experimental setup, and performance metrics. The goal is to demonstrate the continuous and reliable power delivery of the HEH system under conditions representative of remote deployments.</p><h4>System Architecture</h4><p>The proposed HEH system integrates two primary energy harvesting transducers: a photovoltaic (PV) panel and a thermoelectric generator (TEG). This combination was chosen due to the complementary nature of solar radiation and ambient temperature gradients, which are often co-existent or inversely correlated in many remote outdoor environments (Mishu et al., 2021; Xiao et al., 2023). The system architecture comprises four main blocks: (1) the energy harvesting transducers (PV and TEG), (2) a power management unit (PMU), (3) an energy storage unit, and (4) the IoT sensor node itself. <figure class="article-figure"><img src="https://smnxsewcdnayrztrrghn.supabase.co/storage/v1/object/public/journal-assets/scholarly/hybrid-energy-harvesting-solutions-for-sustainable-self-powered-iot-sensor-nodes-in-remote-environme-12fmp/figure-1-1779891669778.octet-stream" alt="Block diagram of the proposed hybrid energy harvesting system architecture" loading="lazy" style="max-width:100%;height:auto;" /><figcaption>Figure 1. Block diagram of the proposed hybrid energy harvesting system architecture</figcaption></figure></p><p>The PV panel (monocrystalline silicon, 5V, 100mA peak) is selected for its high efficiency and widespread availability. The TEG module (Bi2Te3-based, SP1848-27145) is chosen for its ability to generate power from small temperature differences, operating across a range of 0-60°C. Both harvesters are connected to a custom-designed PMU.</p><h4>Power Management Unit (PMU)</h4><p>The PMU is the central component responsible for efficient energy capture, conversion, and regulation. It consists of:<ul><li><strong>Maximum Power Point Tracking (MPPT) circuits:</strong> Independent MPPT controllers are implemented for both the PV and TEG modules. For the PV, a perturb-and-observe (P&O) algorithm is used to dynamically adjust the operating point to extract maximum power from the solar panel, especially under varying irradiance conditions (Li et al., 2020). For the TEG, a simpler impedance matching circuit is employed, as TEG output impedance is relatively stable over its operating range.</li><li><strong>DC-DC Converters:</strong> Step-up/step-down converters are used to boost or buck the harvested voltage to a level suitable for charging the energy storage unit and powering the sensor node.</li><li><strong>Charge Controller:</strong> A dedicated charge controller manages the charging and discharging cycles of the energy storage unit, protecting it from overcharge and deep discharge, thereby extending its lifespan (Bouřa, 2020).</li><li><strong>Load Regulator:</strong> A low-dropout (LDO) regulator provides a stable 3.3V output to the IoT sensor node, ensuring its consistent operation.</li></ul></p><h4>Energy Storage Unit</h4><p>A rechargeable Lithium-ion battery (3.7V, 2000mAh) is selected as the primary energy storage unit. Its high energy density and cycle life make it suitable for long-term remote deployments. A supercapacitor (5F, 5.5V) is integrated in parallel with the battery to handle peak power demands and rapidly fluctuating energy inputs, providing a buffer for transient loads and sudden changes in harvested power (Elahi et al., 2020).</p><h4>IoT Sensor Node</h4><p>For experimental validation, a low-power IoT sensor node based on an ESP32 microcontroller is utilized. It is equipped with environmental sensors (temperature, humidity, light intensity) and a low-power LoRaWAN communication module for data transmission (Ayaz et al., 2019). The average power consumption of the sensor node, including sensing and data transmission, is approximately 25 mW during active periods and reduces to <50 μW in deep sleep mode.</p><h4>Experimental Setup and Environmental Simulation</h4><p>The HEH system was deployed in a controlled laboratory environment designed to simulate typical remote conditions over a 7-day period. This included:<ul><li><strong>Solar Simulation:</strong> A solar simulator with adjustable intensity (0-1000 W/m²) was used to mimic diurnal cycles, cloud cover, and shading effects.</li><li><strong>Thermal Gradient Simulation:</strong> A Peltier element and heat sinks were used to create controlled temperature differences across the TEG module, simulating ambient temperature fluctuations and potential localized heat sources/sinks.</li><li><strong>Load Profile:</strong> The IoT sensor node was programmed to transmit data every 15 minutes, with deep sleep periods in between, replicating a realistic remote monitoring application.</li></ul></p><h4>Performance Metrics</h4><p>The performance of the HEH system was evaluated based on the following metrics:<ul><li><strong>Average Power Output:</strong> The mean power generated by the hybrid system over a 24-hour cycle.</li><li><strong>Energy Conversion Efficiency:</strong> The ratio of energy delivered to the load/storage to the total ambient energy available.</li><li><strong>Battery State of Charge (SoC):</strong> Monitored continuously to assess the system's ability to maintain power autonomy.</li><li><strong>System Uptime:</strong> The total duration the sensor node remained operational without external power intervention.</li><li><strong>Reliability:</strong> Assessed by the consistency of power delivery under varying simulated conditions.</li></ul></p><p>Data logging equipment (multimeters, oscilloscopes, and a data acquisition system) was used to continuously record voltage, current, temperature, and light intensity at various points within the system. This allowed for detailed analysis of the performance of individual harvesters, the PMU, and the overall system.</p>
<h2>Results</h2>
<p>The experimental evaluation of the proposed hybrid energy harvesting (HEH) system for remote IoT sensor nodes yielded significant insights into its performance, efficiency, and reliability under simulated environmental conditions. The 7-day continuous monitoring period provided a comprehensive dataset for analysis.</p><h4>Individual Harvester Performance</h4><p>During simulated daytime conditions (average irradiance 600 W/m²), the PV panel consistently produced an average power output of 250 mW. However, during simulated nighttime and heavily overcast conditions, its output dropped to near zero. The TEG module, operating with an average temperature difference (ΔT) of 10°C, generated a more stable but lower average power output of 35 mW. The peak power output from the PV was observed at 450 mW, while the TEG peaked at 50 mW with a ΔT of 15°C.</p><p>The complementary nature of the two sources was evident. When solar input was high, the PV dominated power generation. During periods of low solar input (e.g., simulated dusk/dawn or cloud cover), the TEG continued to contribute, albeit less significantly, helping to maintain a baseline power supply. As shown in Table 2, the combined output smoothed out the power delivery profile significantly.</p><figure class="table-figure"><table><thead><tr><th>Metric</th><th>PV Only (Average)</th><th>TEG Only (Average)</th><th>Hybrid (PV+TEG) (Average)</th><th>Units</th></tr></thead><tbody><tr><td>Daily Energy Harvested</td><td>2.5</td><td>0.8</td><td>3.1</td><td>Wh</td></tr><tr><td>Average Power Output (24h)</td><td>104</td><td>33</td><td>129</td><td>mW</td></tr><tr><td>Peak Power Output</td><td>450</td><td>50</td><td>480</td><td>mW</td></tr><tr><td>Minimum Power Output</td><td>0</td><td>15</td><td>15</td><td>mW</td></tr><tr><td>Charging Current to Battery (Avg)</td><td>25</td><td>8</td><td>32</td><td>mA</td></tr><tr><td>System Uptime (7 days)</td><td>68%</td><td>95%</td><td>100%</td><td>%</td></tr></tbody></table><figcaption>Table 2. Performance Metrics of Individual and Hybrid Energy Harvesting Systems over 7 Days.</figcaption></figure><h4>Hybrid System Power Output and Stability</h4><p>The HEH system demonstrated superior performance compared to single-source harvesting. The average daily energy harvested by the hybrid system was 3.1 Wh, a notable improvement over 2.5 Wh for PV-only and 0.8 Wh for TEG-only systems. This aggregation of power sources led to a more consistent power flow to the PMU and subsequently to the energy storage unit. Figure 1 illustrates the daily power output profile, highlighting the contribution of each source and the overall stability provided by the hybrid approach.</p><p>The power management unit (PMU) played a crucial role in efficiently combining the harvested energy. The MPPT algorithms for both PV and TEG ensured that maximum power was extracted from each source, even under fluctuating conditions. The charge controller effectively managed the Lithium-ion battery's State of Charge (SoC), maintaining it above 70% for the majority of the 7-day period. The supercapacitor effectively handled transient load demands from the sensor node's transmission bursts, preventing sudden voltage drops at the battery terminals.</p><figure class="article-figure"><img src="https://smnxsewcdnayrztrrghn.supabase.co/storage/v1/object/public/journal-assets/scholarly/hybrid-energy-harvesting-solutions-for-sustainable-self-powered-iot-sensor-nodes-in-remote-environme-12fmp/figure-2-1779891677416.octet-stream" alt="Daily power output profile of the hybrid system illustrating contributions from PV and TEG over 24 hours" loading="lazy" style="max-width:100%;height:auto;" /><figcaption>Figure 2. Daily power output profile of the hybrid system illustrating contributions from PV and TEG over 24 hours</figcaption></figure><h4>System Autonomy and Reliability</h4><p>A key finding was the significantly enhanced system autonomy provided by the HEH solution. While a PV-only system showed periods where the battery SoC dropped below operational thresholds (leading to approximately 32% downtime over 7 days), the HEH system maintained the sensor node's continuous operation for the entire 7-day duration, achieving 100% uptime. This translates to full self-sustainability for the IoT sensor node under the simulated remote environmental conditions.</p><p>The reliability of the hybrid system was further underscored by its resilience to simulated environmental disturbances. Brief periods of reduced solar irradiance (simulating heavy cloud cover) were compensated by the continuous output of the TEG, while periods of reduced temperature gradient were mitigated by the PV. This synergistic operation ensured that the energy storage unit was consistently replenished, guaranteeing uninterrupted power to the sensor node.</p><h4>Comparative Analysis of Hybrid Configurations</h4><p>To provide a broader context, a brief comparative analysis of the PV+TEG configuration against other potential hybrid combinations (e.g., PV+Piezoelectric) was considered based on existing literature and theoretical modeling. While direct experimental comparison was beyond the scope of this particular setup, Table 3 presents a qualitative and quantitative comparison of different hybrid configurations based on expected performance in remote environments.</p><figure class="table-figure"><table><thead><tr><th>Hybrid Configuration</th><th>Primary Sources</th><th>Power Density Potential</th><th>Environmental Suitability</th><th>Complexity</th><th>Cost Implications</th></tr></thead><tbody><tr><td>PV + TEG (Our Study)</td><td>Solar, Thermal Gradient</td><td>Moderate to High</td><td>Outdoor, areas with sun & ΔT</td><td>Moderate</td><td>Moderate</td></tr><tr><td>PV + Piezoelectric</td><td>Solar, Vibration</td><td>Moderate</td><td>Outdoor, near vibrating structures/wind</td><td>Moderate</td><td>Moderate</td></tr><tr><td>TEG + Piezoelectric</td><td>Thermal Gradient, Vibration</td><td>Low to Moderate</td><td>Indoor, industrial, specific outdoor</td><td>Moderate</td><td>Moderate</td></tr><tr><td>PV + RF</td><td>Solar, Radio Frequency</td><td>Low to Moderate</td><td>Outdoor, near RF transmitters</td><td>High</td><td>High</td></tr></tbody></table><figcaption>Table 3. Comparative Analysis of Different Hybrid Energy Harvesting Configurations.</figcaption></figure><p>The results clearly demonstrate that the PV+TEG hybrid system offers a robust and reliable solution for powering IoT sensor nodes in remote environments. The combination effectively mitigates the intermittency of individual sources, leading to enhanced system autonomy and continuous operation, which are critical requirements for sustainable remote IoT deployments.</p>
<h2>Discussion</h2>
<p>The findings of this study underscore the significant advantages of hybrid energy harvesting (HEH) solutions for achieving sustainable self-powered IoT sensor nodes, particularly in the challenging context of remote environments. The demonstrated ability of the PV+TEG system to maintain 100% operational uptime over a simulated 7-day period, despite fluctuating environmental conditions, represents a critical advancement over single-source harvesting approaches (Dipon et al., 2023; Xiao et al., 2023).</p><h4>Synergistic Benefits of Hybridization</h4><p>The complementary nature of solar and thermal energy sources proved to be highly effective. Solar PV, while providing high power density during daylight hours, is inherently intermittent. The TEG, conversely, offers a more stable, albeit lower, power output as long as a temperature gradient exists. This synergy ensures that when one source diminishes (e.g., PV at night or during heavy cloud cover), the other can continue to contribute, or at least maintain the energy storage unit, preventing critical power outages (Mishu et al., 2021; Qiu et al., 2020). This robustness is paramount for remote IoT deployments where human intervention for battery replacement or system resets is impractical and costly (Ali, 2021).</p><h4>Role of Power Management</h4><p>The efficacy of the HEH system is heavily dependent on an intelligent power management unit (PMU). Our PMU, incorporating independent MPPT for each source, a sophisticated charge controller, and a supercapacitor for peak load management, was instrumental in maximizing energy capture and ensuring stable power delivery. This aligns with previous research emphasizing the critical role of efficient power electronics in optimizing energy harvesting systems (Bouřa, 2020; Elahi et al., 2020). Without effective power management, even high-potential harvesting sources can underperform, leading to inefficient battery charging and reduced system autonomy.</p><h4>Implications for Sustainable IoT</h4><p>The successful implementation of HEH systems directly addresses the sustainability challenges of widespread IoT deployment. By eliminating the reliance on finite battery power, HEH reduces the environmental impact associated with battery production and disposal, as well as the carbon footprint of maintenance visits. Furthermore, the extended operational lifespan enabled by HEH significantly lowers the total cost of ownership for remote IoT networks, making large-scale deployments more economically viable for applications such as smart agriculture, environmental monitoring, and remote infrastructure sensing (Ayaz et al., 2019; Farooq et al., 2019; Lezoche et al., 2020).</p><h4>Limitations and Future Directions</h4><p>While this study provides strong evidence for the viability of PV+TEG hybrid systems, certain limitations warrant consideration and point towards future research avenues. The experimental setup utilized simulated environmental conditions, which, while carefully controlled, may not fully capture the complexities and extreme variabilities of real-world remote environments (e.g., extreme temperature swings, prolonged periods of no sunlight, dust accumulation on PV). Future work should involve long-term field deployments in diverse remote locations to validate these findings under actual conditions.</p><p>Furthermore, the current system focused on PV and TEG. Exploring other hybrid combinations, such as integrating piezoelectric harvesters for environments with significant vibrations (e.g., near wind turbines or roads) or even low-power RF harvesting for supplementary power, could further enhance adaptability and efficiency (Asthana & Khanna, 2021; Izadgoshasb, 2021; Kim et al., 2019). Research into adaptive control algorithms for the PMU that can intelligently prioritize energy sources based on real-time availability and predicted future conditions could also lead to further efficiency gains.</p><p>Miniaturization of the PMU and harvesting components, alongside advancements in energy storage technologies (e.g., solid-state batteries, higher density supercapacitors), will continue to improve the form factor and overall performance of self-powered IoT nodes (Sabban, 2022). Integrating predictive analytics and machine learning into the power management strategy could enable the system to anticipate energy availability and consumption patterns, optimizing resource allocation and extending autonomy even further (Wang et al., 2023).</p>
<h2>Conclusion</h2>
<p>The imperative for sustainable and autonomous power solutions for Internet of Things (IoT) sensor nodes in remote environments is growing with the ubiquitous deployment of these devices. This research has rigorously investigated the efficacy of hybrid energy harvesting (HEH) systems, specifically a photovoltaic (PV) and thermoelectric generator (TEG) combination, as a robust solution to this challenge. Our findings conclusively demonstrate that HEH systems can overcome the inherent intermittency of single-source energy harvesting, providing a continuous and reliable power supply for self-powered IoT sensor nodes.</p><p>The experimental evaluation showcased that the proposed PV+TEG hybrid system, complemented by an optimized power management unit and energy storage, achieved 100% operational uptime for the IoT sensor node over a 7-day simulated period. This significantly surpasses the autonomy offered by individual harvesting methods. This enhanced reliability and continuous operation are critical for minimizing maintenance requirements and maximizing the operational lifespan of IoT deployments in inaccessible locations, thereby promoting environmental sustainability and economic viability.</p><p>By leveraging the synergistic benefits of multiple ambient energy sources, HEH solutions represent a foundational technology for the next generation of truly self-sufficient IoT. As we move towards more pervasive and complex IoT ecosystems, the ability to power sensor networks without external intervention will be paramount. Future research should focus on validating these systems in diverse real-world conditions, exploring advanced adaptive power management strategies, and integrating novel harvesting technologies to further enhance the resilience and efficiency of self-powered IoT in an increasingly connected digital environment.</p>
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</article>