Journal of Renewable Energy and Smart Device
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<![CDATA[The Smart Battery Safety and Anti-Theft Monitoring System for Electric Bicycles with Automatic Cut-Off and Dual-Channel Notification ]]>
<![CDATA[Perdana, Andhika Putra]]>;
<![CDATA[Tsani, Mokhammad Rifqi]]>;
<![CDATA[Wibowo, Helmi]]>;
<![CDATA[Widiandaru, Nanang Okta]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.685
<![CDATA[The rapid growth of electric bicycle usage in Indonesia has been accompanied by rising safety incidents, particularly those related to battery thermal runaway and theft. This research presents the design and implementation of an integrated monitoring and security system for electric bicycles using the ESP32 microcontroller, PZEM-017, DS18B20, and Neo-6M GPS module, combined with a web-based dashboard and Telegram bot notification. The system was developed using the Research and Development (R&D) method with a four-parameter monitoring scheme covering voltage, current, temperature, and geospatial coordinates. Experimental results from twenty data points per sensor demonstrated excellent accuracy: DS18B20 achieved an average error of 1.133%, PZEM-017 achieved 1.224% for voltage and 1.787% for current, while the Neo-6M module achieved 0.000575% and 0.000042% for latitude and longitude respectively. The automatic cut-off mechanism successfully operated in all six tested scenarios, and the Telegram-website integration delivered notifications with an average delay of two seconds. These findings confirm that the proposed system improves safety and security of electric bicycles through real-time multi-parameter monitoring and remote intervention capability. Unlike prior systems that address monitoring or security in isolation, this work is the first to unify real-time multi-parameter battery protection, automatic cut-off, geofencing, and dual-channel notification within a single low-cost ESP32-based platform tailored for urban electric bicycle users in Indonesia. The practical relevance of this integration is particularly significant given the accelerating adoption of electric bicycles as primary short-distance transportation in densely populated Indonesian cities, where charging-related fire incidents and theft cases have reached critical levels. ]]>
<![CDATA[AI-Assisted PID Tuning for Voltage Control of an Axial-Flow Pico-Hydro Generator ]]>
<![CDATA[Ali, Machrus]]>;
<![CDATA[Hidayatul Nurohmah]]>;
<![CDATA[Muhammah Agil Haikal]]>;
<![CDATA[Yanuar Mahfudz Safarudin]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.691
<![CDATA[Pico hydropower is a renewable-energy option for isolated communities and low-head run-of-river sites, but axial-flow pico-hydro generators are vulnerable to voltage fluctuation when water flow, hydraulic head, or consumer load changes. This study proposes a novel and reproducible artificial-intelligence-assisted proportional-integral-derivative (PID) tuning framework for voltage control of a 220 V, 2 kW axial-flow turbine generator ZD760-LM-(18-20). The novelty lies in combining a voltage-control-oriented small-signal model of a low-head axial-flow pico-hydro unit, a nonminimum-phase hydraulic zero that represents inverse initial response, identical bounded PID-search constraints, and a composite objective that explicitly penalizes inverse dip, overshoot, settling time, ITAE, and IAE. The plant model combines actuator or electronic-load-controller dynamics, non-elastic water-column dynamics, turbine-generator dynamics, and sensor dynamics. PID gains obtained from Ziegler-Nichols (PID-ZN), Ant Colony Optimization (PID-ACO), and Particle Swarm Optimization (PID-PSO) are compared under Kp = 0-100, Ki = 0-50, and Kd = 0-10. Simulation results show that PID-ZN stabilizes the plant but requires a 6.80 s settling time and produces an ITAE of 2.9603. PID-ACO reduces settling time to 2.26 s and ITAE to 1.1320, whereas PID-PSO gives the lowest ITAE of 1.1311 with only 0.030% overshoot. Compared with PID-ZN, PID-PSO reduces settling time by 66.8% and ITAE by 61.8%. These results indicate that AI-based PID tuning can improve voltage quality in low-cost rural and off-grid pico-hydro systems using practical ELC or simple actuator implementations.]]>
<![CDATA[RTC-Scheduled ESP32 IoT Prototype for Automated Hydroponic Nutrient Irrigation ]]>
<![CDATA[Nurohmah, Hidayatul]]>;
<![CDATA[Soni Setiawan, Dafit]]>;
<![CDATA[Ali, Machrus]]>;
<![CDATA[Ciptian Weried Priananda]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.694
<![CDATA[Reliable nutrient circulation is essential for small-scale hydroponic cultivation, but many Internet of Things (IoT) hydroponic systems depend on multi-parameter sensing, cloud-based decision making, or artificial-intelligence-assisted architectures that can be costly and difficult to reproduce in household and educational settings. This study designs and functionally evaluates a low-cost real-time-clock (RTC)-assisted ESP32 IoT prototype for scheduled hydroponic nutrient irrigation. The practical contribution is a reproducible entry-level automation baseline that helps household users, school laboratories, and community demonstration sites maintain predictable nutrient circulation without continuous manual checking. The system integrates an ESP32 microcontroller, DS3231 RTC, DHT11 temperature-humidity sensor, relay-driven DC nutrient pump, LCD, and Blynk monitoring interface. The main novelty is the use of battery-backed RTC scheduling as a local-first mechanism for routine nutrient-pump actuation, while the cloud dashboard is retained for supervision rather than as the sole timing dependency. This position differentiates the prototype from cloud-centered hydroponic systems whose irrigation execution may depend on network availability. The prototype was programmed to activate the nutrient pump at 07:00 and 16:00 for 10 s per event. Functional validation used four dimensions: environmental reading consistency, RTC timing consistency, pump actuation reliability, and IoT monitoring availability. Daytime DHT11 observations ranged from 29.1 to 31.2 °C and 62 to 68% RH, with mean values of 30.28 °C and 64.50% RH. The RTC showed a recorded 0-s difference from the daily reference time over five observation days within the resolution of the test. The pump executed all observed scheduled ON-OFF events, yielding 100% schedule execution success for two scheduled activations and 100% relay-pump state reliability for four observed states. The Blynk interface displayed temperature, humidity, and pump status during testing. These results demonstrate engineering feasibility for a reproducible scheduled nutrient-irrigation baseline suitable for household-scale hydroponic practice, student laboratories, and introductory IoT learning. The scope is deliberately bounded to prototype-level engineering feasibility: the study evaluates scheduling, actuation, and monitoring, but does not claim nutrient-dosing precision, flow-rate calibration, pH/EC regulation, or crop-yield improvement. Future work should include calibrated reference instruments, pH/EC and flow-rate measurement, nutrient-volume accuracy testing, network-performance analysis, power and cost benchmarking, and controlled plant-growth trials.]]>
<![CDATA[LNG-Based Decarbonization of Small-Scale Maritime Transport: A Technical and Economic Feasibility Study in North Kalimantan ]]>
<![CDATA[Nari, Henny Pasandang]]>;
<![CDATA[Kim, Yong Wong]]>;
<![CDATA[Sirman, Mahadir]]>;
<![CDATA[Sumardiawan, Romy]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.700
<![CDATA[Indonesia's vast natural gas reserves present a strategic opportunity to decarbonise its maritime sector, particularly in archipelagic regions such as North Kalimantan, where small wooden and fiberglass vessels rely on high-cost, high-emission diesel fuels, posing environmental and economic challenges. This study employed a mixed-methods approach, combining fuel consumption simulations with stakeholder surveys and interviews to evaluate the technical, economic, and policy feasibility of adopting liquefied natural gas (LNG) for non-conventional inter-island vessels. The technical analysis compared LNG and biodiesel performance on a Mitsubishi 89 kW marine engine regarding thermal efficiency, specific fuel consumption (SFC), and operational costs. Simulation results show that LNG-powered engines achieved 46.46% thermal efficiency and an SFC of 0.140 kg/kWh, compared to 33.85% and 0.1847 kg/kWh for biodiesel. An economic feasibility analysis across eight inter-island routes demonstrated fuel cost savings of 51–68% with LNG relative to biodiesel, with an estimated simple payback period of 3.2–4.5 years for dual-fuel engine retrofitting under baseline fuel price assumptions. Stakeholders acknowledged LNG's benefits but raised concerns about infrastructure limitations and regulatory readiness. This study concludes that LNG adoption for non-conventional vessels is economically and environmentally viable, particularly when aligned with Indonesia's broader energy transition strategies, and provides a scalable model for other archipelagic maritime regions seeking to reduce emissions and fuel dependency.]]>
<![CDATA[Development of a Modern Smart Agricultural System Based on IoT and Artificial Intelligence ]]>
<![CDATA[Denny Irawan]]>;
<![CDATA[Shofitri Juliana Setiyohadi]]>;
<![CDATA[Dewi Dewanti Subrata]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.702
<![CDATA[Abstract – Modern agriculture faces challenges in increasing productivity, efficiency, and sustainability, especially in horticultural commodities such as chilies that have high economic value. The efficiency in question includes the use of increasingly limited land for urban communities. This study proposes the integration of specific multisensor for comprehensive soil parameter monitoring with adaptive decision-making algorithms for chili cultivation in narrow urban areas. The Internet of Things (IoT) is used to monitor environmental conditions in real-time, such as temperature, soil moisture, pH, and nutrient levels (Nitrogen, Phosphorus, and Potassium), through sensors integrated with a wireless network based on the Blynk application and a camera module for early detection of diseases and pests. The collected data is then analysed and processed by a microcontroller using a precise Artificial Intelligence (AI) algorithm, namely the Fuzzy Logic algorithm, to monitor and control land conditions. The integration of IoT and AI is able to increase the efficiency of water and fertilizer use up to 90% of the standard, reduce the risk of crop failure, and improve the quality of chili production results where on the 90th day, chili plants have begun to bear fruit with a fruit diameter at the base of more than 1 cm, a fruit length of more than 3 cm, a stem diameter at the base of about 1 cm, many branches and dense leaves. Compared to conventional agricultural systems, the relevance obtained for urban farmers is: democratization of precision agriculture, optimization of operational costs, real-time risk mitigation, and independent food security. The novelty of this research is the use of adaptive AI Fuzzy Logic, and the integration of visual detection (camera) in one urban ecosystem resulting in high water and fertilizer use efficiency and providing a new contribution in the form of democratization of precision agriculture where industrial-level technology is simplified into a modular ecosystem that is affordable for urban communities. The system that has been built has a structure that allows for development to a broader level including: a modular ecosystem, commodity adaptability, cloud and big data integration, and the potential for vertical farming.]]>
<![CDATA[Modelling and Simulation of Multistep Constant Current Fast Charging for Lithium-Ion Batteries Using a PID Controlled Synchronous Buck Converter ]]>
<![CDATA[Fahmi, Monika]]>;
<![CDATA[Deni Tri Laksono]]>;
<![CDATA[Dedi Tri Laksono]]>
<![CDATA[ Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/joresd.v3i2.708
<![CDATA[High-current fast charging of lithium-ion batteries in electric motorcycles is challenged by current instability, voltage overshoot, and accelerated degradation caused by nonlinear electrochemical and thermal dynamics. Conventional single-stage buck converters exhibit limited capability in maintaining precise current regulation across wide state-of-charge (SoC) variations, thereby constraining both efficiency and operational safety. This study proposes a novel adaptive multistep constant-current (MS-CC) fast charging framework specifically tailored for electric motorcycle applications, implemented using a PID-controlled synchronous buck converter. Unlike existing MS-CC approaches, the proposed method introduces a unified control architecture that dynamically schedules five discrete current levels based on real-time voltage thresholds, enabling seamless transition between charging stages without inducing transient spikes. The system is modeled and validated in MATLAB/Simulink, with PID parameters tuned via the Ziegler–Nichols closed-loop method. Simulation results show that the charging current accurately tracks its reference within 0.25% across all stages, with negligible overshoot and stable transient performance. From a practical standpoint, the proposed strategy aligns with the operational constraints of electric motorcycles, such as compact onboard chargers, limited thermal management capacity, and frequent fast-charging cycles. Furthermore, the method reduces switching and conduction losses, mitigates thermal stress, and enhances overall charging efficiency while preserving electrochemical stability. These findings demonstrate that the proposed MS-CC control scheme not only advances the state-of-the-art in charging control strategies but also provides a viable, implementation-ready solution for next-generation electric motorcycle charging systems.]]>
