INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)  
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025  
Review Paper on Advanced Floating Robotic System for Water  
Quality Monitoring  
Mr.Aviraje Bhosale, Ms.Tejashree Sakhale, Ms.Rahi Jadhav, Mr.Nishant Gaikwad  
Dr. A. R. Nichal  
Department of E & TC, Adarsh Institute of Technology & Research Centre Vita, India  
DOI: https://dx.doi.org/10.51244/IJRSI.2025.12110008  
Received: 10 November 2025; Accepted: 20 November 2025; Published: 27 November 2025  
ABSTRACT:  
Among all the emerging global environmental issues, the deterioration of water quality is of prime importance  
because it directly affects human health, aquatic ecosystems, and industrial processes. Traditional methods of  
manual sampling and laboratory-based analysis have intrinsic limitations due to high labor costs, low sampling  
frequency, and no real-time insights. As a result of recent developments within autonomous systems, IoT, and  
embedded sensing technologies, the development of advanced floating robotic systems with the capability of  
continuous automated monitoring of water bodies has been possible. These can integrate multi-parameter  
sensors, wireless data communication, GPS navigation, and intelligent processing units for collection and  
transmission of key water quality indicators like pH, turbidity, dissolved oxygen, temperature, and conductivity.  
This review paper presents a comprehensive analysis of the technological evolution, design methodologies, and  
current state-of-the-art floating robotic platforms for water quality monitoring. The study will analyze the  
strengths and limitations of several sensor configurations, communication protocols, power management  
techniques, and robotic designs adopted in recent research. It further discusses the major challenges:  
environmental interference, sensor calibration issues, biofouling, power limitations, and long-term deployment  
constraints. By comparing the existing systems and identifying technological gaps, this paper looks into future  
opportunities comprising AI-based predictive analytics, low-cost sensor innovations, energy harvesting, and  
fully autonomous navigation. Conclusively, the study finds that floating robotic systems hold great promise for  
transforming real-time water quality assessment and thereby offering substantial support toward sustainable  
water resource management.  
Keywords: Floating robotic system, Water quality monitoring, IoT sensors, Autonomous navigation,  
Environmental monitoring  
INTRODUCTION  
Water quality degradation has become one of the most critical environmental challenges due to rapid industrial  
growth, urban expansion, agricultural runoff, and inefficient wastewater management. Pollutants increasingly  
enter natural water bodies, leading to severe ecological damage, reduced biodiversity, and significant risks to  
human health. Traditional water-quality monitoring methods depend heavily on manual sampling and laboratory  
analysis, which, although accurate, suffer from several drawbacks such as delayed results, limited spatial  
coverage, high operational costs, and the inability to detect sudden real-time fluctuations.  
Recent advancements in IoT devices, embedded controllers, autonomous robotics, and long-range  
communication networks have enabled the development of floating robotic platforms for automated water-  
quality assessment. These systems integrate sensors such as pH, dissolved oxygen, turbidity, temperature, and  
conductivity along with wireless technologies including GSM, LoRa, Wi-Fi, and ZigBee. Unlike fixed station-  
based monitoring, floating robots can navigate across water surfaces, collect distributed samples, detect spatial  
variations, and transmit data continuously to cloud platforms.  
Despite these promising developments, floating robotic systems still face challenges such as sensor drift during  
long-term deployment, biofouling on sensor surfaces, unstable communication in remote locations, limited  
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INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)  
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025  
battery capacity, and disruptions caused by water currents and floating debris. Moreover, the selection of  
appropriate sensors, power-management strategies, and reliable communication modules remains a crucial  
design consideration for ensuring long-term operational efficiency.  
In recent years, researchers have increasingly focused on combining autonomous navigation with intelligent data  
processing to enhance system accuracy and reliability. Modern systems are exploring energy-harvesting  
techniques, multi-parameter sensor calibration, and AI-based analytics to improve predictive capabilities.  
Therefore, it is essential to critically examine the latest technological advancements, compare existing robotic  
solutions, and highlight the research gaps that need attention for developing more efficient and scalable water-  
monitoring platforms.  
BASIC BLOCK DIAGRAM  
1. Design of Floating Platform  
The first step is to design a buoyant, light floating structure that could operate on various water surfaces.  
Materials often used to make these structures buoyant and durable include PVC, acrylic sheets, HDPE, or  
3Dprinted plastic. The design includes isolated chambers for electronics, batteries, sensors, and optionally solar  
panels. For autonomous movement, propulsion units can be included, such as DC motors or servo driven rudders.  
2. Integration of Water Quality Sensors  
The robotic platform is equipped with necessary sensors according to the requirements of different projects.  
Commonly used sensors include pH, turbidity, DO, temperature, and electrical conductivity. The sensors are  
housed in a dedicated chamber, wherein the water comes into direct contact with the sensors while protecting  
the internal electronics. Calibration using standard solutions is done to achieve accurate, real-time readings  
before actual deployment.  
Design of Floating  
Platform  
Communication and  
Data Transmission  
Integration of Water  
Quality Sensors  
Basic Block  
Diagram  
Data Acquisition and  
Processing  
Embedded Electronics  
and Power System  
Fig No.1 – Basic architecture of a floating robotic water quality monitoring system.  
3. Embedded Electronics and Power System  
It normally consists of one embedded processor or microcontroller, such as Arduino, ESP32, Raspberry Pi, or  
STM32, managing sensor data, controlling motors, and communicating. The power system usually consists of  
rechargeable lithium batteries, sometimes complemented with solar panels for extended operation. Voltage  
regulators, waterproof connectors, and protective casings are used to maintain system safety and performance.  
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INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)  
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025  
4. Data Acquisition and Processing  
Sensor readings are acquired through analog or digital interfaces and then processed for filtering to remove noise  
or erroneous data. The conversion of raw sensor values occurs into standard measurement units, such as pH, °C,  
NTU, and mg/L. Some systems implement data averaging or the detection of outliers to improve the accuracy  
of readings. Data can be stored locally on an SD card or processed further for applications in real time.  
5. Communication and Data Transmission  
It involves the use of different communication technologies to transmit water quality data, depending on the  
deployment environment.  
Wi Fi for shortrange monitoring  
Bluetooth for local testing and device configuration  
GSM/GPRS for long range mobile connectivity SIM800, SIM900  
LoRa for low power, long distance transmission  
GPS modules for location tracking and mapping  
The processed data is then sent to the cloud platforms or custom dashboards for real time visualization and  
analysis.  
LITERATURE REVIEW  
Water quality monitoring using floating robotic systems has been a fast-growing field of research during the last  
decade, driven by enabling technologies in IoT, autonomous navigation, and miniaturized sensing. While most  
early works relied on static buoy-based systems, recent studies have emphasized mobility, multi sensor  
integration, and real time data transmission.  
An early prototype of the floating buoy system with basic sensors for pH and temperature measurement was  
developed by Sharma et al. 2018. The system used simple RF communication, limiting the range of operation  
but demonstrating the feasibility of low cost water monitoring platforms.  
Gharat et al. (2019) proposed an IoT enabled buoy system using a GSM module for water quality data  
transmission from a distance. Their design significantly improved communication flexibility but unfortunately  
lacked the possibility of navigation itself and was also capable of providing only point based measurements, thus  
limiting its usage in larger water bodies.  
Kumar and Singh (2020) designed a solar powered, autonomous floating robot that would be capable of  
monitoring several parameters: pH, temperature, and dissolved oxygen. Their effort leaned toward sustainability  
and renewable energy, while pointing out problems concerning sensor drift over long deployment.  
Rahman et al. (2020) proposed a compact floating robot with Wi Fi communication integrated with a cloud-  
based dashboard. Though real time visualization was excellent in their system, its use was limited to network  
availability areas, hence restricting its deployment in remote water bodies.  
Bhardwaj & Mehta, 2020, discussed low-cost sensor networks integrated with Arduino based floating modules.  
The design demonstrated that even low budget hardware is able to deliver reliable results; however, accuracy  
decreased when the surrounding environment was either highly polluted or highly turbid, causing saturation in  
the sensors.  
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INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)  
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025  
Sivaraman et al. (2021) conducted an experiment with the LoRa long range communication systems. The floating  
unit successfully transmitted the data over more than 3 km with low power consumption. However, the system  
faced difficulties in transmitting large datasets and required stable gateways for continuous operation.  
Ullah et al. (2021) proposed a solar powered floating platform with automated motorized propulsion. Their  
research emphasized dynamic sampling, whereby the robot patrols across different zones of a lake. This  
approach improved the spatial coverage, but battery management and motor endurance are the key limitations  
of the approach.  
Zhou et al. (2022) introduced a multi node collaborative robotic system wherein small floating units  
communicate and coordinate their actions in a mesh network. This networked approach increased data density  
and improved the accuracy through spatial interpolation; however, synchronization among nodes was complex  
and computation heavy.  
Patil et al. (2021) extended the earlier systems by incorporating GPS and ZigBee communication for spatial  
mapping of water quality in larger areas. Although data latency and dependency on line of sight communication  
remained major limiting factors, this system provided higher coverage.  
Chen et al. (2022) integrated AI driven analytics into floating robotic systems, bringing predictive modeling and  
automated anomaly detection into operation. The platform adopted machine learning algorithms to improve data  
interpretation but required a computational load that is provided by more powerful processors onboard, thus  
increasing the cost and energy consumption.  
Santos et al. (2022) developed a catamaran style floating robot equipped with ultrasonic sensors that could detect  
obstacles and plan autonomous routes. This increased stability and mobility made it fit for dynamic river  
environments; however, strong currents and debris present in the environment often interfered with the accuracy  
of navigation.  
Li and Zhang (2023) focused on long term monitoring using antibiofouling coating and self cleaning mechanisms  
in underwater sensors. The results indicated the increased long term lifetime of sensors at greater manufacturing  
costs and system complexity. Recent research, in 20232024, has also started embracing hybrid robotic systems  
that incorporate surface floating platforms together with underwater drones for multi depth monitoring. These  
systems provide superior vertical profiling but also have important challenges related to coordination and energy  
consumption, and waterproofing electronics.  
Recent research (2024) has involved the integration of edge computing into floating robots to allow onboard  
data processing to reduce delay and bandwidth usage. These systems can provide early warnings for spikes in  
pollution, but with higher computational demands, stronger processors and higher capacity batteries are required.  
CRITICAL ANALYSIS OF LITERATURE  
A deeper evaluation of existing studies reveals several important insights beyond the descriptive summaries  
presented in the literature review.  
1. Communication Technology Trade-offs  
Different communication modules show distinct advantages and limitations. GSM-based systems offer long-  
range communication but lack navigation capabilities. Wi-Fi-based robots provide real-time dashboards yet are  
confined to limited coverage areas. LoRa systems ensure long-range and low-power operation but cannot  
efficiently send large datasets.  
2. Power and Operational Endurance  
Solar-powered platforms increase deployment duration; however, their performance decreases during cloudy  
weather or monsoon seasons. Robots with propulsion systems experience high power consumption, forcing  
researchers to compromise between mobility and energy efficiency.  
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INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)  
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025  
3. Sensor Accuracy and Stability  
Low-cost sensors commonly used in budget-friendly systems tend to lose accuracy in highly polluted or turbid  
environments. Long-term deployments often experience sensor drift, biofouling on sensor surfaces, and reduced  
reliability of readings.  
4. Autonomous Navigation Limitations  
Although GPS and ultrasonic sensors improve navigation, environmental challenges such as floating debris,  
strong currents, and wave disturbances limit precision. Reliable autonomous route planning is still  
underdeveloped in most studies.  
5. Advanced Systems Introduce New Challenges  
AI-enabled and mesh-network systems allow predictive analysis and multi-robot coordination but increase  
system complexity, energy demand, and overall cost.  
ANALYTICAL CONCLUSION  
No existing system optimally balances mobility, long-range communication, sensor durability, energy  
efficiency, and cost. This gap highlights the need for hybrid power solutions, improved sensor calibration  
techniques, and robust intelligent navigation mechanisms.  
LITERATURES ANALYSIS  
The comparative study shows that existing floating robotic systems offer significant advancements in  
communication, energy efficiency, and autonomous monitoring. However, most systems still face challenges  
such as limited coverage, high energy demand, complex coordination, and reduced sensor accuracy over long  
term deployment. Overall, the literature highlights the need for a more robust, long range, and low maintenance  
water monitoring solution.  
Table No. 1 Comparative Result Analysis of Existing Floating Robotic Systems  
Author Name  
Advantages  
Limitations  
& Year  
• IoT enabled buoy system  
• No navigation feature  
Gharat et al. (2019) • GSM based long distance data transfer  
• Improved communication flexibility  
• Only point based measurements  
• Not suitable for large water bodies  
• Solar powered autonomous robot  
• Sensor drift over long deployment  
• Reduced accuracy with time  
Kumar & Singh  
• Measures pH, temperature  
(2020)  
• Promotes renewable energy use  
• Compact floating robot  
• Works only in Wi Fi coverage areas  
Rahman et al.  
• Wi Fi communication  
(2020)  
• Not suitable for remote locations  
• Realtime cloud dashboard  
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INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)  
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025  
Author Name  
& Year  
Advantages  
Limitations  
• Low cost Arduino based system  
• Reliable basic monitoring  
• Lower accuracy in polluted water  
• Sensor saturation in high turbidity  
Bhardwaj & Mehta  
(2020)  
• Budget friendly solution  
• Long range LoRa communication (>3 km)  
• Very low power consumption  
• Suitable for large areas  
• Cannot send large datasets  
• Needs stable LoRa gateways  
Sivaraman et al.  
(2021)  
• Solar powered robotic platform  
• Battery management issues  
• Limited motor endurance  
• Motorized propulsion for dynamic  
sampling  
Ullah et al. (2021)  
• Better spatial coverage  
• Multi node mesh networking  
• Higher data density  
• Complex node synchronization  
• High computational load  
Zhou et al. (2022)  
Patil et al. (2021)  
Chen et al. (2022)  
• Better spatial interpolation  
• GPS + ZigBee communication  
• Large area spatial mapping  
• Better coverage  
• Data latency problems  
• Line of sight dependency  
• AI based analytics  
• High processor requirement  
• Predictive modelling  
• Increased cost and energy usage  
• Automated anomaly detection  
• Stable catamaran design  
• Affected by strong currents  
Santos et al. (2022) • Ultrasonic obstacle detection  
• Autonomous route planning  
• Debris reduces navigation accuracy  
• Antibiofouling sensor coating  
• High manufacturing cost  
Li & Zhang (2023) • Self cleaning mechanism  
• Longer sensor lifespan  
• Increased design complexity  
• Surface + underwater monitoring  
• Coordination complexity  
• High energy requirement  
• Waterproofing challenges  
Hybrid Systems  
• Multidepth water profiling  
(2023–2024)  
• Improved vertical analysis  
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INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)  
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025  
Author Name  
& Year  
Advantages  
Limitations  
• Onboard data processing  
• High computational demand  
Edge Computing  
(2024)  
• Reduced transmission delay  
• Early pollution spike detection  
• Requires larger battery capacity  
FUTURE RESEARCH ROADMAP  
The analysis highlights several promising directions for enhancing next-generation floating robotic water-  
monitoring systems:  
1. Adaptive Sampling Techniques  
Developing algorithms that dynamically adjust sampling frequency based on detected pollution changes can  
improve data relevance and optimize energy usage.  
2. Federated and Distributed Learning  
Multiple robots can collaboratively train machine-learning models without transmitting raw data, reducing  
bandwidth usage and allowing large-scale predictive monitoring.  
3. Hybrid USV AUV Monitoring  
Integrating surface robots with underwater vehicles will enable multi-depth water profiling and more  
comprehensive environmental analysis.  
4. Anti-Biofouling & Self-Cleaning Mechanisms  
Incorporating coatings, ultrasonic cleaning, or mechanical wiping can significantly extend sensor lifespan during  
long-term deployments.  
5. Energy Harvesting Innovations  
Hybrid solar–hydro or wave-powered systems can support continuous monitoring and power-consuming  
components like motors and AI processors.  
6. TRL (Technology Readiness Level) Evaluation  
Assigning TRLs to different system types can help determine their maturity level and suitability for deployment  
in real-world conditions.  
CONCLUSION  
Advanced floating robotic systems represent an efficient and reliable technological means for continuous and  
real time water quality monitoring. Such robotic platforms are able to cover larger areas compared with  
traditional manual samplings, imply less labor, and allow quicker detection of the changes in water conditions.  
The integration of multiparameter sensors, wireless communication, and a microcontroller based control unit  
enables such systems to operate autonomously and provide accurate environmental data.  
The review of existing research shows significant progress in areas such as sensor accuracy, power management,  
and autonomous navigation. Solar powered designs, GPS based path planning, and cloud connected dashboards  
have further improved usability and long term performance in these systems. However, some challenges remain;  
these are sensor calibration, biofouling, harsh weather conditions, and limited battery life.  
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INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)  
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025  
In all, floating robotic systems hold immense promise for environmental monitoring and smart water  
management in the future. Further developments in sensor technology, AI based data analysis, and energy  
efficient designs will see these systems playing a key role in early pollution detection, ecosystem protection, and  
sustainable management of water resources.  
Despite progress, the majority of existing systems struggle with long-term autonomous deployment due to  
energy constraints and biofouling-related sensor degradation. Addressing these challenges is crucial for scaling  
these robots into large water-management networks.  
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