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Article

A Low-Cost Autonomous Multi-Functional Buoy for Ocean Currents and Seawater Parameter Monitoring, and Particle Tracking

by
Zachary Williams
1,*,
Manuel Soto Calvo
1,
Han Soo Lee
1,2,3,*,
Morhaf Aljber
3 and
Jae-Soon Jeong
2
1
Coastal Hazards and Energy System Science Laboratory, Transdisciplinary Science and Engineering Program, Graduate School of Advanced Science and Engineering, Hiroshima University, 1-5-1 Kagamiyama, Higashi-Hiroshima 739-8529, Hiroshima, Japan
2
Center for the Planetary Health and Innovation Science (PHIS), The IDEC Institute, Hiroshima University, 1-5-1 Kagamiyama, Higashi-Hiroshima 739-8529, Hiroshima, Japan
3
Smart Energy Field, Graduate School of Innovation and Practice for Smart Society, Hiroshima University, 1-5-1 Kagamiyama, Higashi-Hiroshima 739-8529, Hiroshima, Japan
*
Authors to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2025, 13(9), 1629; https://doi.org/10.3390/jmse13091629
Submission received: 16 July 2025 / Revised: 18 August 2025 / Accepted: 23 August 2025 / Published: 26 August 2025
(This article belongs to the Special Issue Monitoring of Ocean Surface Currents and Circulation)
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Abstract

Low-cost ocean monitoring systems are increasingly needed to address data gaps in coastal environments, particularly in regions where traditional research infrastructure is limited. This paper presents the design, development, and field deployment of a biophysical ocean buoy (BOB)—a compact, solar-powered autonomous buoy system capable of measuring sea surface temperature, salinity (via electrical conductivity), total dissolved solids, pH, and GPS position. The system features real-time data transmission via the Iridium satellite, local data logging, and modular sensor integration. The BOB was deployed for three missions in the Seto Inland Sea, Japan, ranging from 26–56 h in duration. The system successfully recorded high-resolution environmental data, revealing coastal gradients, diurnal heating cycles, and tidal current reversals. Over 95% of the measurements were successfully recovered, and the Iridium communications exceeded 90% reliability. The temperature and salinity data captured fine-scale variations consistent with freshwater plume interactions and tidal forcing. With a total system cost under USD 2000 and minimal deployment requirements, the BOB offers a scalable solution for distributed ocean monitoring. Its performance suggests strong potential for use in aquaculture monitoring, coastal hazard detection, and climate change research, especially in data-sparse regions. This work contributes to the growing field of democratized ocean observation, combining affordability with operational reliability.

1. Introduction

The world’s oceans cover more than 70% of the Earth’s surface and serve as the planet’s primary climate regulator, driving global weather patterns, absorbing atmospheric CO2, and redistributing heat across latitudes [1]. These marine systems face unprecedented pressures from climate change, with rising sea surface temperatures, ocean acidification from increasing atmospheric CO2 levels, and changing circulation patterns that threaten marine ecosystem stability [2,3,4]. Marine pollution compounds these climate pressures, with an estimated 8 million metric tonnes of plastic entering marine environments annually combined with chemical contaminants and runoff from nutrients that create widespread hypoxic zones [5,6]. Coastal ecosystems, including seagrass beds, estuaries, and nearshore habitats, are particularly vulnerable, as they experience the direct convergence of climate impacts and intensive human activities; however, these regions are critical for carbon sequestration, fisheries productivity, and marine biodiversity [7,8,9].
Various monitoring strategies have been deployed to address the challenge of ocean observation, operating across multiple scales and platforms [10,11]. Satellite remote sensing provides global coverage for sea surface temperature, chlorophyll concentrations, and surface currents through missions such as MODIS, Sentinel-3, and Landsat, although with limitations in cloud-covered regions and surface-only measurements [12]. The Argo Float network has revolutionized deep ocean monitoring, with over 4000 autonomous profiling floats collecting temperature and salinity data worldwide, providing unprecedented insights into ocean heat content and circulation patterns [13,14]. Fixed buoy networks, including the Global Ocean Observing System (GOOS) stations and regional networks such as the National Data Buoy Center, provide continuous time series data at specific locations [15]. Research vessel campaigns complement these platforms with detailed biogeochemical sampling and process studies, although they remain spatially and temporally limited due to operational costs [16,17].
Despite these monitoring efforts, current existing buoy systems suffer from fundamental limitations that severely constrain their effectiveness and deployment scope [18,19]. The Global Drifter Program, while providing valuable surface data across ocean basins, completely lacks subsurface measurement capabilities and offers no real-time data transmission for immediate response to changing conditions, limiting its utility for time-sensitive environmental monitoring [20]. European Smart Buoy systems, although designed for comprehensive biogeochemical monitoring, require prohibitively expensive maintenance schedules, specialized technical support, and frequent sensor calibrations that limit their widespread use and long-term sustainability [21]. The Japanese TRITON buoy network and similar research-grade platforms illustrate the cost barrier problem—each unit requires substantial investment in deployment, maintenance, and data retrieval, making large-scale networks economically infeasible for most research institutions and developing nations [22]. Most critically, the existing systems fail to address the monitoring gap in coastal waters, where Argo floats cannot operate due to shallow depths, where traditional moorings are vulnerable to damage from fishing activities and storms, and where satellite observations cannot penetrate to capture subsurface biogeochemical processes essential for understanding ecosystem health and water quality [18,23,24].
Recent advances in sensor miniaturization, low-power electronics, and wireless communication technologies offer promising pathways to overcome these monitoring constraints [25,26]. Affordable, high-accuracy sensors for temperature, salinity, and dissolved solids now enable continuous multi-parameter monitoring at a fraction of the traditional costs, with improvements in sensor stability and drift characteristics reducing the calibration requirements [27]. Energy-efficient microcontrollers and improved battery technologies, including lithium-ion and energy harvesting systems, can support long-term autonomous operations spanning months to years without intervention [28,29]. Advanced satellite communication modules, including the Iridium and LoRaWAN networks, provide real-time data transmission capabilities that were previously limited to expensive research platforms, enabling immediate data access and emergency response capabilities [30,31]. GPS tracking integration allows for simultaneous water mass tracking and platform location monitoring, addressing both Eulerian and Lagrangian observation needs while providing critical data for understanding coastal circulation patterns [32,33]. These technological convergences create opportunities for developing cost-effective monitoring solutions that can operate reliably in challenging coastal environments while providing the spatial and temporal resolution necessary for understanding local ecosystem dynamics [34,35].
To address these challenges and to leverage the emerging technologies, we present the development of a biophysical ocean buoy (BOB), a low-cost autonomous multi-functional buoy designed specifically for the continuous monitoring of coastal and nearshore environments. The BOB integrates temperature, electrical conductivity, and pH sensors with GPS tracking capabilities, providing real-time subsurface water quality data and particle tracking functionality in a single, economically viable platform. By combining affordable sensor technology with efficient wireless data transmission, the BOB aims to fill the critical monitoring gap in coastal waters while offering a scalable solution for establishing the dense monitoring networks that were previously cost-prohibitive. This development represents a significant step toward expanding ocean monitoring capabilities and enabling comprehensive observations of the coastal environment and ecosystems most vulnerable to climate change and human impacts.
The novelty of this work lies not only in its low cost, but in its combination of modular, open-hardware design, real-time Iridium satellite telemetry, and reliance on globally available off-the-shelf components within a compact, solar-powered platform. Unlike most commercial drifters, the system transmits raw sensor data, enabling flexible post-deployment calibration and quality control. This approach allows for the same platform to be adapted to different monitoring priorities, such as dissolved oxygen, chlorophyll-a, or turbidity, through straightforward sensor substitutions, lowering the barriers to entry for researchers and educators in both the developed and developing regions.

2. Materials and Methods

The BOB was engineered for modularity (interchangeable sensor suite and electronics), affordability (total build cost under USD 2000), and reliability (tested for waterproofing and satellite transmission stability) under short-term oceanographic field deployments. This section outlines the design, construction, and testing of a low-cost, autonomous seawater buoy developed for monitoring temperature, salinity, and surface drift in the Seto Inland Sea.
The development and deployment of the buoy system followed a series of structured steps. The process began with devising monitoring plans, which included defining the parameters to be measured and determining the deployment strategy. This was followed by the design of the circuit and the careful selection of appropriate electronic components. Once the components were acquired, circuit testing was conducted to ensure functionality and compatibility.
The outer components of the buoy, including the housing and structural parts, were subsequently constructed. These materials were designed to protect the electronics in harsh marine conditions. Following the assembly, a series of tests were conducted on individual components and communication protocols, including data transmission via satellites.
To ensure seaworthiness, the buoy underwent leakage and water ingress tests to validate the integrity of the housing under simulated field conditions. With these tests completed, the fully assembled buoy was deployed in a pond for an integrated systems test. This allowed for real-world validation of the buoy’s performance in a controlled environment.
After successful testing, the buoy was deployed in its final field location. Following deployment, the system was retrieved for post-mission evaluation. Feedback from this deployment was used to guide decisions on potential improvements and refinements for future iterations of the system.

2.1. System Design and Architecture

Figure 1 shows the design of a BOB with a half-spherical shape and a hexagonal top to accommodate 6 solar cells and a transparent lid. The cylindrical pipe extends from the base where the sensors are housed.
The buoy uses commercially available off-the-shelf sensors for temperature, conductivity, pH, and GPS, with data transmitted via the Iridium satellite. The estimated total cost for a single buoy, excluding one-time capital equipment, such as a 3D printer or soldering tools, is approximately USD 2000. While the components are generally commercially available, access and cost may vary in developing countries due to local supply chains or import regulations. The system’s modular design allows for substitution with equivalent locally available sensors or electronics, which can facilitate replication and deployment in regions with limited access to specific parts.
Table 1 provides an overview of the essential hardware components selected for the buoy system. It outlines the specific models used, their measurement ranges or accuracy, and important operational notes that influence their integration. These components were chosen to ensure reliable environmental data collection, efficient power management, and robust communication capabilities in the marine environment.
Sensor readings were scheduled using a deep-sleep architecture controlled by a TPL5110 timer. All the data were encoded into compact messages suitable for satellite transmission.
The buoy body was 3D printed using a PET-G filament for mechanical durability and UV resistance. The main structure consists of a spherical float (30 cm diameter), selected to provide sufficient buoyancy and stability while remaining portable, with an integrated sensor pipe (5 cm diameter, 17 cm long) sized to house the EC, temperature, and pH sensors without obstructing flow, extending from the bottom. The top hemisphere incorporates six flat panels arranged in a hexagonal layout for mounting solar cells.
The buoy has a dry weight of 2.9 kg and a total operational weight of 5.6 kg. The housing was sealed with marine-grade epoxy and rubber gaskets to ensure waterproofing, including at the sensor entry points. The solar array was mounted flush to minimize drag and to maximize sunlight exposure.
Deployment configurations supported both moored and drifting modes. For drifting operation, the hydrodynamic form was designed to follow surface currents with minimal rotational instability.

2.1.1. Buoyancy

Buoyancy was calculated via Archimedes’ principle:
Fb = ρsw · g · Vd
where ρsw is the seawater density, g is the gravitational acceleration, and Vd indicates the displaced volume of the buoy. The Vd was estimated by calculating the submerged volume of the buoy below water based on its composite geometry, which includes a hemispherical lower section, a cylindrical sensor pipe extending below, and an upper hexagonal housing assumed to remain above the waterline. Standard geometric volume equations were used to estimate the submerged portion under static equilibrium.
This yielded a required displacement of approximately 0.00546 m3 to support the full system mass in seawater. The simulations indicated a submergence depth of 49.5%, ensuring sufficient freeboard to maintain antenna exposure for satellite transmission and to resist moderate wave splashes. A stability assessment using righting moment calculations, which evaluate the torque generated to return a floating body to the upright position after it is tilted, revealed a positive restoring torque up to tilt angles of 60°, confirming that the center of gravity remained below the center of buoyancy and that the system would self-correct under small perturbations. To validate these results, a prototype was constructed and tested in a controlled tank environment with a full payload to confirm the buoyancy and trim angle stability as predicted.

2.2. Laboratory and Controlled Environment Testing

Calibration and integration tests were carried out to ensure the accuracy and reliability of each sensor integrated into the buoy system. The temperature sensor (DS18B20 probe) was validated against a NIST-traceable thermometer using a water bath with a range of 0–40 °C. The electrical conductivity (EC) sensor was calibrated using standard solutions of 84 μS/cm and 12,880 μS/cm, with temperature compensation enabled to improve measurement precision. Total dissolved solids (TDS) and salinity measurements were verified through comparisons with gravimetric calculations. The pH sensor was calibrated using standard NBS buffers prior to deployment. The sensor measures pH on the NBS scale, which may differ from the total hydrogen ion scale (pHT) used in oceanography. Future validation using spectrophotometric pH measurements of seawater samples is planned to improve accuracy and to enable a comparison with standard marine pH scales. For positioning accuracy, the GPS module was validated against fixed survey markers. The entire buoy assembly underwent waterproofing verification by submersion in freshwater for 4 to 6 h, during which no water ingress was observed, confirming its integrity.
Following laboratory validation, a three-week pond test was conducted at Hiroshima University’s pond facility, Budo Pond (34.40118, 132.71260), to assess the real-time operational performance of the buoy system. The buoy was moored in place, and continuous monitoring of sensor readings, satellite data transmissions via the Iridium network, and power status was performed. The test confirmed waterproof integrity under extended exposure, verified that sensor outputs remained within expected ranges, and demonstrated the successful transmission and receipt of data strings. No issues related to seal degradation or electromagnetic interference were identified during this period.

2.2.1. Energy Balance

The energy system of the buoy consisted of six 12 V, 150 mA photovoltaic cells coupled with a 10 Ah sealed lead acid battery. This configuration provided sufficient power to maintain continuous operation of the sensors and communication subsystems throughout all deployment scenarios. Even during periods of reduced sunlight, such as December deployment, system voltages were maintained above 11.7 V, indicating a positive energy balance. Table 2 summarizes the power consumption and active durations of the various components during a typical 24-h cycle. By implementing a TPL5110 power timer to adjust the duty cycle, the daily energy consumption was reduced to approximately 13.7 Wh. This setup ensures that the buoy remains fully energy autonomous during field deployment.

2.3. Field Deployments in the Seto Inland Sea

The buoy deployments were conducted in the Seto Inland Sea at coordinates 34.2394° N, 132.7945° E. This location was selected because of its moderate tidal flow and mixing characteristics, seasonal freshwater inflows from the nearby Noro River, and its significance for aquaculture and environmental monitoring [36]. Two separate deployment campaigns were carried out in 2024, the first in late spring and the second in winter, to evaluate the seasonal variations in environmental conditions and to assess the buoy’s performance under differing circumstances. The deployments were conducted under variable environmental conditions, ranging from calm and sunny to rainy conditions. Table 3 summarizes the characteristics of the buoys used during these field deployments, including the dates, number of buoys deployed, sensor configurations, deployment durations, sampling intervals, and additional notes. The initial deployment on May 29 involved one buoy equipped with temperature, electrical conductivity (EC), salinity, and GPS sensors, running for approximately 26 h with a 10-min sampling interval to test full system functionality. The December 19 deployments consisted of two buoys: Buoy 2B, which was equipped with a pH sensor in addition to the standard temperature, EC, and GPS sensors, operated for approximately 56 h with a 20-min sampling interval, and Buoy 2A, which lacked the pH sensor and operated for approximately 27 h with the same sampling frequency. These two buoys followed distinct drift paths, providing valuable insights into local current divergence and tidal reversals.
Figure 2 presents a detailed comparison between the buoy system’s energy consumption and its solar power input. The solar-battery power system was tested both in controlled, low-irradiance conditions and during actual field deployment to assess its ability to maintain energy autonomy. To estimate the typical solar input, the historical solar irradiance data for the deployment region in Hiroshima were analyzed. This involved integrating the average daily solar radiation values over the photovoltaic panel’s effective area and efficiency, accounting for seasonal variations and weather patterns. From these calculations, a typical solar energy input of approximately 21.6 Wh per day was derived for the solar panels under normal, moderate sunlight conditions while considering efficiency.
The buoy’s energy consumption was initially estimated via datasheet values for each component’s current draw and their respective active and sleep duty cycles, resulting in a theoretical daily consumption of approximately 13.73 Wh. However, measurements collected during a three-week pond deployment using an INA3221 current sensor indicated that the actual average daily energy usage was closer to 10.20 Wh. This discrepancy can be attributed to several factors as follows: conservative datasheet values often represent worst-case current draws, while real-world duty cycles sometimes allow for longer sleep periods or reduced activity, and environmental factors, such as fewer transmission attempts or sensor readings, reduce the overall consumption.
This lower actual consumption relative to the available solar input provides a comfortable energy margin, securing the buoy’s operational autonomy. Even during periods of reduced sunlight, such as cloudy days or shorter winter days, the system’s power management strategy—which includes using the TPL5110 timer to aggressively switch components to low-power sleep modes—ensures that the battery levels remain stable. Consequently, the buoy maintains continuous operation without power interruption, validating the design approach for energy efficiency in the field.
Before deployment, all buoy systems underwent comprehensive pre-launch testing to verify GPS acquisition, battery voltage levels, and sensor output functionality. The buoys were released from a support vessel under calm and sunny conditions to maximize initial satellite connectivity. Upon release, live data transmission commenced immediately. To minimize electromagnetic interference and power draw, the sensors were activated sequentially: the electrical conductivity (EC) and pH sensors each operated for approximately 15 s, followed by the GPS module running for approximately 90 s. The RockBLOCK satellite model then attempted message transmission for up to three minutes to ensure successful data delivery. Post-deployment inspections revealed no evidence of water ingress or corrosion, with only minimal biofouling on the sensor surfaces.
The quality control procedures used interquartile-range (IQR) statistics to identify potential outliers in each sensor’s time series. Flagged points were visually inspected in the context of deployment conditions, and only those attributable to telemetry errors, sensor startup transients or sudden unrealistic jumps in sensor readings were removed. Sensor drift was evaluated by comparing the stable periods within each deployment and by checking pre- and post-deployment calibration readings against the reference standards. Transmission reliability was assessed by calculating the percentage of successfully received messages relative to those sent. The analytical methods involve a time series analysis to identify the trends in temperature and salinity, trajectory mapping of the buoy drift paths via GPS data overlaid on marine charts, and quantification of system uptime on the basis of the proportion of scheduled readings that were successfully recorded and transmitted.

3. Results

3.1. System Performance and Reliability

Initial laboratory tests confirmed that all the sensors operated within the manufacturer-specific performance metrics. The DS18B20 temperature sensor consistently recorded values within ±0.3 °C of a NIST-traceable thermometer across the 0–40 °C range. The Atlas Scientific EC probe showed less than 1.5% deviation from standard solutions, validating the reliability of the two-point calibration. The pH sensor used in Deployment 2A (Table 3) demonstrated stable outputs within ±0.01 pH units during buffered testing. The integrated system, including microcontroller scheduling, deep sleep cycling, and timed sensor activation, performed reliably during a three-week moored pond deployment. The power system, consisting of a 12 V 10 Ah sealed lead acid battery supported by a six-panel solar array, maintained a system voltage above 11.5 V throughout, validating the solar charging design under partly cloudy conditions.
All three field deployments exhibited high system uptime and successful data recovery. The buoys were programmed to transmit data at fixed intervals—10 min for the first deployment and 20 min for the second deployment.
Deployment 1 (May, 10-min interval): The transmission accuracy was 95.3%. Most transmissions aligned closely with the expected interval, but a few deviations occurred. These were not consecutive, indicating transient issues, such as poor satellite visibility or temporary network congestion. Additionally, delays in acquiring a GPS fix or sensor response times may have contributed to the issues.
Deployment 2A (December, 20-min interval): The transmission accuracy was 82.69%. The timing was generally consistent, with some scattered deviations. As with the first deployment, these deviations likely resulted from brief interruptions in satellite connectivity or from the time required for the GPS module to acquire a positional fix under the field conditions.
Deployment 2B (December with a pH sensor, 20-min interval): The transmission accuracy was 98.65%. The performance was similarly consistent with minor variations. The added pH sensor may have slightly increased the time required for data acquisition or processing but did not significantly affect the overall transmission timing.
Across all deployments, the RockBLOCK device’s reliance on the Iridium satellite connectivity and the time required for the GPS module to obtain a fix were the most likely contributors to the observed delays. Weather conditions, satellite geometry, and internal processing also play a role. Despite these challenges, the system maintained a high level of temporal reliability, as shown in Figure 3.

3.2. Seto Inland Sea Deployment Results

3.2.1. Drift Trajectory Analysis

Three separate buoy deployments were conducted in the Seto Inland Sea: one in May (Deployment 1) and two in December (Deployment 2A and Deployment 2B) 2024. The deployment location was the same for all three, which was off the coast near Takehara, as shown in Figure 4.
The buoys moved in the same general southerly direction but changed direction almost every 5–6 h due to tidal reversals. Two of the buoys docked on the island after approximately 26 h, whereas the 2B buoy from the December deployment, which contained the pH sensor, passed through the channel of the islands and traversed the Seto Inland Sea for approximately 56 h.

3.2.2. Oceanographic Measurements

The buoy recorded sea surface temperatures ranging from 17 °C to 18.94 °C during the May deployment, and during the December deployments, sea surface temperatures were approximately 16 °C, with a low value of 6 °C coming from when the buoy docked on an island. The data exhibited clear diurnal variations, with temperatures peaking in the afternoon hours and dropping slightly to the lowest values in the early morning hours. This pattern aligns with the expected heating and cooling cycle influenced by solar radiation.
Temperature data are critical for understanding the thermal structure of the water column, which influences local marine life and biogeochemical processes. The recorded temperature variations also aid in assessing the impact of climate change on the Seto Inland Sea. The temperature data for the track of the BOB in Figure 5 show that the peak temperature, which correlates to after 14:00, is recorded when the BOB drifted north and began turning in a southwards direction. The lowest temperature recorded was 17 °C at approximately 4:00 on the morning of May 30. The SST has a directly proportional relationship with the other variables measured in the experiment.
Salinity levels measured by the BOB ranged from 29.86 PSU to 34.03 PSU during the May experiment and were also similar for the December deployments, with a slightly larger high point of approximately 38 PSU and a low point of 18 PSU from deployment 2B. The value from 2A was almost zero when it was docked on the island. These values fell within the normal range for the salinity levels of coastal waters in the Seto Inland Sea. There were some fluctuations in the data that correlated with the tidal cycle, with slightly higher salinity levels observed during high tide. While these patterns are consistent with known tidal influences, further data are needed to confirm the specific causes of salinity variation in the study area.
Figure 6 shows the pH data for the period of Deployment 2B during December, ranging from 8.75 to approximately 6.25. Lower values were observed when passing near islands or channels between islands and during the nighttime. These lower pH values could be associated with increased biological activity, potentially linked to the presence of seagrass or algae.

3.3. Cost-Effectiveness Analysis

The total system cost of a BOB is <USD 2000, which is less than that of commercial buoys with similar or lower capabilities. Table 4 shows the comparative costs of the buoys compared with those of the BOB. Commercial buoy B has a lower cost, but with less functionality, as it only provides GPS tracking ability and an external device. SPOT Trace is used for GPS tracking via the Globalstar satellite network, which is powered by AA batteries. Commercial Buoy A is powered by a solar cell with battery backup and uses an Iridium 9602 N transceiver model to transmit messages via the Iridium satellite network. This buoy costs more than its simpler counterpart, commercial buoy B, but it still lacks the ability to measure seawater parameters, such as salinity, as in the case of the BOB.

4. Discussion

4.1. System Performance

The BOB demonstrated exceptional reliability across all field trials in the Seto Inland Sea, with autonomous performance under saltwater immersion, solar charging, and open-water drift, confirming the viability of low-cost, field-deployable sensor platforms for nearshore monitoring [37]. The deployments were conducted under variable environmental conditions, ranging from calm and sunny to overcast and stormy periods. These conditions allowed us to evaluate the buoy’s performance under realistic operating scenarios, including variations in solar charging, wave motion, and telemetry reliability. The system achieved >95% uptime and >90% successful transmissions, exceeding values commonly reported in previous low-power, untethered buoy deployments, where uptime and transmission success typically fall below 90% [38]. This operational performance validates the BOB’s readiness for routine deployments and addresses a critical gap in reliable, cost-effective ocean monitoring infrastructure.
Traditional buoy systems present substantial barriers to widespread adoption, demanding significant infrastructure, including ship-based deployment, costly moorings, and post-retrieval data recovery protocols [39]. The BOB’s design fundamentally shifts this paradigm by enabling rapid deployment with minimal equipment, thereby expanding access to ocean data for small teams and institutions that previously lacked the resources for marine monitoring programs. While data transmission costs via the Iridium satellite communication represent an ongoing operational expense, the real-time benefits, including early event detection and continuous system diagnostics, justify this investment for most operational applications.
The system’s saltwater resilience was achieved through careful material selection, utilizing marine-grade epoxy and 3D-printed PET-G components that demonstrated effective corrosion resistance throughout the test period. This approach builds upon established research showing similar durability in printed polymers for marine applications [40], although long-term biofouling remains an acknowledged challenge requiring future investigation [41].
The BOB’s simultaneous measurement of temperature, salinity, total dissolved solids, and position represents a substantial improvement over conventional GPS-only or single-parameter drifters commonly deployed in coastal research [42]. The system is able to collect data at wide ranging intervals, such as 10–30 min, as implemented in this study; whereas traditional bottle sampling is usually limited to daily or weekly collections, and fixed-moored CTDs often operate at lower frequencies. This higher temporal resolution addresses the limitations in coastal observation networks.
Multi-parameter, mobile measurements are increasingly recognized as essential for resolving the fine-scale mixing processes and estuarine dynamics that govern coastal ecosystem functions [43]. The BOB’s trajectory-based sampling approach enables these critical insights even when lower-cost sensors are utilized, democratizing access to previously expensive oceanographic measurement capabilities. The observed drift reversals occurring at approximately 6–8-h intervals closely matched the modelled tidal cycle characteristics of semi-enclosed seas, such as the Seto Inland Sea [44], with field-based validation studies confirming the dominant role of tidal advection in controlling nearshore salinity fronts and freshwater plume dynamics.
This demonstrated performance becomes particularly significant when considered alongside the BOB’s economic advantages and potential for global deployment.

4.2. Affordability and Applications in Coastal Monitoring

Commercial buoys equipped with equivalent sensors and communication features typically cost upwards of USD 10,000 [45], creating substantial barriers to deployment in budget-limited regions where coastal monitoring is often most urgently needed. The BOB’s construction cost of less than USD 2000, as of 2024, represents an order-of-magnitude reduction that enables cost-effective sensor networks in developing coastal nations, directly addressing global inequities in ocean observation infrastructure [46].
This price point strategically aligns with international efforts to democratize ocean sensing, a movement emphasizing open-source, modular platforms that can be locally manufactured and maintained [43]. The BOB fills a critical niche by combining affordability, operational autonomy, and live telemetry capabilities that were previously available only in high-end commercial systems.
The platform significantly outperforms many drifters utilized in past coastal monitoring programs, which often lack multisensor capability [47,48]. The incorporation of expandable sensor options, including potential pH monitoring, positions the BOB for future environmental monitoring applications, such as coastal acidification and pollution concerns, as they intensify globally [49].
These combined advantages of performance and affordability directly enable the transformative applications in coastal monitoring that were previously inaccessible to many institutions. The BOB high-resolution measurements of salinity and temperature provide essential data for pollution detection, aquaculture monitoring, and river plume tracking, all of which are fundamental to effective coastal hazard management strategies [50]. Early detection capabilities for changes in these parameters enable rapid responses to environmental events, including sewage discharge, industrial runoff, or upwelling anomalies, that can significantly impact coastal ecosystems and human communities.
In developing nations, the chronic lack of long-term coastal environmental data represents a major impediment to climate change resilience planning and adaptive management [51]. Tools such as the BOB enable community-led or university-supported data collection initiatives that are both scalable and locally manageable, fostering capacity building in regions where it is most critically needed.
Specific operational applications include monitoring thermal habitat conditions for commercially important fisheries species, such as snapper and sardine, providing essential boundary condition data for hydrodynamic models in ports and estuarine systems, and supporting compliance monitoring for environmental permits associated with coastal infrastructure development projects.
The BOB directly addresses persistent data inequality issues in the Global South, where many coastal regions lack even the basic environmental observations necessary for informed resource management [47]. By dramatically reducing system costs, the BOB supports citizen science models and community-based monitoring programs, empowering local stakeholders to monitor pollution events, temperature extremes, or critical biological cycles, such as fish spawning periods.
The system’s design prioritizes interoperability through standardized data formats, including time-stamped, GPS-tagged measurements that integrate seamlessly with national and regional ocean databases, such as the Global Ocean Observing System (GOOS) and the Copernicus Marine Environment Monitoring Service (CMEMS). Distributed BOB networks could provide crucial supplementary data to satellite observations through high-frequency in situ measurements, addressing spatial and temporal gaps in current monitoring capabilities.
Successful implementation requires the consideration of several factors, including simplified training protocols for deployment and troubleshooting, minimal regulatory constraints (already demonstrated through field testing in Japanese waters), and robust digital infrastructure utilizing platforms, such as Cloudloop or open MQTT brokers for data management. Clear quality assurance protocols, including standardized calibration procedures and automated outlier detection systems, are essential to ensure data reliability and scientific credibility.
The integration of GPS positioning, real-time satellite communication, and multiparameter sensing in the BOB directly addresses the fundamental limitations of the existing coastal monitoring systems outlined in previous research. Traditional approaches suffer from a lack of subsurface measurement capability, prohibitively high operational costs, or dependence on physical retrieval for data access [52,53,54]. The BOB represents a convergence of recent advances in sensor miniaturization, energy efficiency, and satellite connectivity that now enables coastal nations and small institutions to develop effective, autonomous monitoring programs. As anthropogenic pressures on marine systems continue to intensify globally, such affordable and scalable monitoring tools will be essential for filling critical observational gaps and supporting evidence-based coastal management decisions.
While the BOB’s capabilities position it for widespread deployment, several limitations identified during development must be addressed to fully realize this potential.

4.3. Limitations

While the BOB system achieved its core objectives—real-time, multiparameter, low-cost ocean monitoring—several limitations were identified during the development and deployment:
  • Sensor biofouling and drift: Although the sensors performed within specifications during short-term deployments, biofouling risk and long-term drift have not been systematically addressed. Without antifouling measures or regular calibration, prolonged operation may lead to data degradation, particularly in nutrient-rich or warm coastal waters. Additionally, the duration of drifting deployments cannot be predetermined, as each unit’s trajectory depends on currents, wind, and other environmental factors. Unlike moored systems, drifting buoys may reach docking locations at unpredictable times, making long-term in situ monitoring inherently variable.
  • Data transmission constraints: The Iridium satellite communication ensures global coverage, but transmission costs restrict the volume and frequency of data that can be sent. Larger payloads or more frequent updates significantly increase the operational expenses.
  • Mechanical durability: The buoy hull, constructed from 3D-printed PET-G plastic, withstood deployment conditions in calm seas, but rougher offshore environments may exceed its structural limits. The electronics housing and seals were tested in freshwater and limited saltwater exposure but were not pressure-tested beyond shallow conditions.
  • No real-time command capability: The system lacks two-way communication for remote reconfiguration or diagnostics during deployment. If transmission errors or sensor failures occur, recovery must wait until physical retrieval.
  • The pH measurements in this study were obtained using the NBS scale without spectrophotometric validation through discrete bottle samples. This may introduce systematic differences when compared to oceanographic datasets that use the pHT scale.
These identified limitations directly inform our development priorities and expansion plans for the BOB.

4.4. Future Work

Several areas of improvement and expansion are planned for future development of the BOB system:
  • Sensor suite expansion: Future versions will include additional parameters, such as dissolved oxygen, chlorophyll-a (via fluorescence), turbidity, and nitrate sensors, to broaden the biogeochemical monitoring capabilities. Modular firmware and housing support plug-and-play expansion through standard sensor interfaces: I2C (Inter-Integrated Circuit) and UART (Universal Asynchronous Receiver/Transmitter), enabling straightforward integration of additional sensors.
  • Biofouling mitigation: Coatings (e.g., copper mesh or silicone paint), mechanical wipers, or UV-based antifouling will be explored to reduce the impact of marine growth on sensor performance during extended deployments.
  • Improved communication flexibility: Different communication systems will be investigated to lower the costs of satellite communication. Methods such as LTE communications will be investigated as alternatives.
  • Two-way communication and diagnostics: Implementing command-and-control capability would allow operators to update sampling intervals, request diagnostic data, or remotely shut down subsystems for energy conservation.
  • To investigate long-term performance factors, such as biofouling and sensor drift, a moored configuration of the buoy will be tested. This configuration will allow for controlled multi-week to multi-month monitoring while preserving the buoy’s low cost, modular architecture.
  • Future iterations of the buoy deployment will incorporate seawater-based Tris buffer calibration to improve comparability with standard oceanographic datasets.
  • Incorporation of spectrophotometric pH measurements for accuracy validation and proper scale conversion.
  • Field network testing: Deployment of a multi-buoy array for spatially distributed observations will be conducted to assess the BOB’s performance in dynamic estuarine systems and to validate its utility for coastal process studies.

5. Conclusions

In developing a BOB—a biophysical ocean buoy—we demonstrate that an affordable, solar-powered, multi-sensor platform can achieve real-time, high-resolution environmental data collection in complex nearshore settings. With temperature, salinity, and pH sensors, along with GPS tracking and Iridium communications, the BOB addresses both the biogeochemical and physical monitoring needs of coastal managers and researchers. In addition to its affordability, the system’s modularity, raw data transmission capability, and reliance on readily available components distinguish it from most existing drifter platforms. These features support a wider range of applications, facilitate integration into local fabrication workflows, and enhance adaptability for diverse environmental monitoring needs.
The system successfully completed 26- to 56-h autonomous deployments in the Seto Inland Sea, capturing the dynamic changes associated with tides, river plumes, and diurnal cycles. Its consistent transmission success (>90%) and sensor performance within the specifications validate the operational reliability of low-cost marine sensors. Critically, the total build cost, under USD 2000, and simplified deployment procedures make the BOB accessible to institutions in developing countries, student-led research programs, and citizen science initiatives.
By combining emerging technologies—low-power microcontrollers, robust open-source sensors, and real-time satellite telemetry—this work advances the broader efforts to democratize ocean observations. The BOB represents a scalable, replicable, and impactful tool for expanding environmental monitoring precisely in coastal regions that are most vulnerable to climate change and anthropogenic pressures.
The success of the BOB demonstrates that coastal ocean monitoring does not require high-cost infrastructure or large amounts of institutional support. By addressing these limitations through iterative design and testing, the BOB platform can evolve into a scalable system for ecosystem monitoring, early warning applications, and community-led coastal stewardship in data-scarce regions.

Author Contributions

Conceptualization, Z.W., M.S.C. and H.S.L.; methodology, Z.W. and M.S.C.; software, Z.W.; validation, Z.W., M.S.C. and H.S.L.; formal analysis, Z.W.; investigation, Z.W., M.S.C.; resources, H.S.L.; data curation, Z.W.; writing—original draft preparation, Z.W.; writing—review and editing, Z.W., M.S.C., H.S.L., M.A. and J.-S.J.; visualization, Z.W., M.S.C., H.S.L., M.A. and J.-S.J.; supervision, H.S.L.; project administration, H.S.L.; funding acquisition, H.S.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research is supported by Grants-in-Aid for Scientific Research (B) (Grant No. 24K00991) from the Japan Society for the Promotion of Science (JSPS) and Japan–Sweden MIRAI Project Seed Funding.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AUVAutonomous Underwater Vehicle
BOBBiophysical Ocean Buoy
CMEMSCopernicus Marine Environment Monitoring Service
CTDConductivity, Temperature, Depth
ECElectrical Conductivity
GOOSGlobal Ocean Observing System
GNSSGlobal Navigation Satellite System
GPSGlobal Positioning System
I2CInter-Integrated Circuit
LTELong Term Evolution
MQTTMessage Queue Telemetry Transport
NGONon-Governmental Organization
NMEANational Marine Electronics Association
PET-GPolyethylene Terephthalate Glycol
PPMParts per Million
PPTParts per Thousand
PSUPractical Salinity Units
SISSeto Inland Sea
SGSpecific Gravity
SLASealed Lead Acid
SSTSea Surface Temperature
TDSTotal Dissolved Solids
UARTUniversal Asynchronous Receiver/Transmitter
UVUltraviolet

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Jmse 13 01629 g001
Figure 1. Biophysical ocean buoy (BOB) design showing prototype model (right) and expanded version with additional sensor capacity (left). (Photo credit: Author).
Figure 1. Biophysical ocean buoy (BOB) design showing prototype model (right) and expanded version with additional sensor capacity (left). (Photo credit: Author).
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Figure 2. Energy budget analysis for the BOB deployment showing cumulative energy consumption by system components (temperature sensor, salinity sensor, pH sensor, GPS, and satellite communication) compared to solar energy input over the deployment period.
Figure 2. Energy budget analysis for the BOB deployment showing cumulative energy consumption by system components (temperature sensor, salinity sensor, pH sensor, GPS, and satellite communication) compared to solar energy input over the deployment period.
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Figure 3. Communication protocol performance showing transmission intervals between successive data messages and expected operational duration for each BOB deployment.
Figure 3. Communication protocol performance showing transmission intervals between successive data messages and expected operational duration for each BOB deployment.
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Figure 4. Study area map showing the BOB deployment locations in the Seto Inland Sea near Takehara, Japan. Deployment 1 (May 2024, green line), Deployment 2A (December 2024, orange line), and Deployment 2B (December 2024, purple line).
Figure 4. Study area map showing the BOB deployment locations in the Seto Inland Sea near Takehara, Japan. Deployment 1 (May 2024, green line), Deployment 2A (December 2024, orange line), and Deployment 2B (December 2024, purple line).
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Figure 5. Temporal variations in water temperature (°C) and salinity (PSU) recorded during the BOB deployments: (a) Deployment 1 (29–30 May 2024), (b) Deployment 2A (December 2024), and (c) Deployment 2B (December 2024).
Figure 5. Temporal variations in water temperature (°C) and salinity (PSU) recorded during the BOB deployments: (a) Deployment 1 (29–30 May 2024), (b) Deployment 2A (December 2024), and (c) Deployment 2B (December 2024).
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Figure 6. The pH measurements from Deployment 2B in the Seto Inland Sea during December 2024.
Figure 6. The pH measurements from Deployment 2B in the Seto Inland Sea during December 2024.
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Table 1. Hardware components and specifications for the BOB construction 1.
Table 1. Hardware components and specifications for the BOB construction 1.
ComponentModelRange/AccuracyKey Features
Temperature sensorDallas DS18B20±0.5 °C, 0.0625 °C resolutionWaterproof, 1–12-bit resolution
EC probeAtlas Scientific K 1.0 + EZO-EC circuit0.07–50,000 μS/cm, ±2%Auto temperature compensation
pH sensorAtlas Scientific Gen 3 + EZO-pH0–14, ±0.002 accuracyIsolated circuit, marine grade
GPS moduleQuectel L76K2.5 m CEP, 1 Hz updateMulti-GNSS, low power mode
Satellite modemRockBLOCK 9603340-byte messagesGlobal Iridium coverage
MicrocontrollerESP32-WROOM240 MHz dual-coreDeep sleep capability
Power supply12 V 10 Ah SLA battery-6 × 12 V 150 mA solar panels
1 Accuracy and resolution values are taken from manufacturer datasheets. The specified ranges and accuracies reflect the manufacturer specifications under laboratory conditions; in situ performance may differ due to environmental factors and deployment duration.
Table 2. Daily energy budget for the BOB electronic components.
Table 2. Daily energy budget for the BOB electronic components.
ComponentActive Time/DayCurrent (mA)Energy Use (Wh/day)% of Total
ESP32 microcontroller4 h1607.6856.1%
Satellite modem (RockBLOCK)4 h1004.8035.0%
GPS module1.2 h460.664.8%
Temperature Sensor24 h1.50.433.1%
EC Probe12 min500.120.9%
pH Sensor12 min18.30.0440.3%
Total 13.7 Wh/day100%
Table 3. The BOB deployment summary and configuration details.
Table 3. The BOB deployment summary and configuration details.
DeploymentDateSensors IncludedDurationSampling IntervalNotes
#129 May 2024Temp, EC, Salinity, GPS~26 h10 minInitial test of full system functionality
#2A19 December 2024Temp, EC, Salinity, GPS~27 h20 minSame location, without pH
#2B19 December 2024Temp, EC, Salinity, GPS, pH~56 h20 minExtended test, included pH
Table 4. Comparison of the costs of pre-made purchased buoys to the overall cost involved in the construction of the BOB.
Table 4. Comparison of the costs of pre-made purchased buoys to the overall cost involved in the construction of the BOB.
BuoyBase Cost (Approx. USD)Tracking Cost (USD)Total Cost (USD)Measured ParametersCommunication MethodNotes
Commercial buoy A3400Included3400Position onlyIridium satelliteFull unit cost including tracking
Commercial buoy B485 8851370Position onlyGlobalstar satellite networkCost split reflects optional tracking device
BOB (this study)1810Included1810Position, Temp., salinity, EC, pHIridium satelliteIncludes integrated sensors and Iridium modem
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MDPI and ACS Style

Williams, Z.; Soto Calvo, M.; Lee, H.S.; Aljber, M.; Jeong, J.-S. A Low-Cost Autonomous Multi-Functional Buoy for Ocean Currents and Seawater Parameter Monitoring, and Particle Tracking. J. Mar. Sci. Eng. 2025, 13, 1629. https://doi.org/10.3390/jmse13091629

AMA Style

Williams Z, Soto Calvo M, Lee HS, Aljber M, Jeong J-S. A Low-Cost Autonomous Multi-Functional Buoy for Ocean Currents and Seawater Parameter Monitoring, and Particle Tracking. Journal of Marine Science and Engineering. 2025; 13(9):1629. https://doi.org/10.3390/jmse13091629

Chicago/Turabian Style

Williams, Zachary, Manuel Soto Calvo, Han Soo Lee, Morhaf Aljber, and Jae-Soon Jeong. 2025. "A Low-Cost Autonomous Multi-Functional Buoy for Ocean Currents and Seawater Parameter Monitoring, and Particle Tracking" Journal of Marine Science and Engineering 13, no. 9: 1629. https://doi.org/10.3390/jmse13091629

APA Style

Williams, Z., Soto Calvo, M., Lee, H. S., Aljber, M., & Jeong, J.-S. (2025). A Low-Cost Autonomous Multi-Functional Buoy for Ocean Currents and Seawater Parameter Monitoring, and Particle Tracking. Journal of Marine Science and Engineering, 13(9), 1629. https://doi.org/10.3390/jmse13091629

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