Review Article
Smart Monitoring and Control Systems in Bioreactor-Based Aquaculture Water Treatment
Alebachew Molla*
Issue:
Volume 13, Issue 2, December 2025
Pages:
22-32
Received:
7 September 2025
Accepted:
18 September 2025
Published:
10 October 2025
Abstract: This abstract presents a concise overview of smart monitoring and control systems for aquaculture water treatment. It highlights the critical safety and productivity challenges faced by aquaculture due to fluctuations in essential water quality parameters such as temperature, pH, dissolved oxygen, and ammonia. Traditional water quality monitoring methods are often labor-intensive and intermittent, risking suboptimal conditions and economic losses. The advent of Internet of Things based smart systems, integrating diverse sensors, cloud computing, and automated actuators, enables real-time, continuous water quality monitoring and dynamic control. These systems facilitate remote data access, efficient management, and rapid response to environmental changes, enhancing fish health and optimizing bioreactor performance. Furthermore, incorporation of artificial intelligence and machine learning offers predictive analytics that improve decision-making and enable proactive interventions. Practical deployments demonstrate significant benefits such as reduced labor costs, improved resource utilization, and enhanced sustainability. Challenges in sensor robustness, data security, and cost remain, but ongoing advances in low-cost, energy-efficient sensors and integrated biosensing technologies promise wider adoption. Overall, smart monitoring and control technologies represent a transformative step toward fully automated, data-driven aquaculture systems, promoting a sustainable blue economy while meeting the growing global demand for aquatic food resources. This review encompasses current technologies, applications, challenges, case studies, and future directions in this dynamic field, offering valuable insights for researchers, practitioners, and policy makers aiming to advance sustainable aquaculture water management.
Abstract: This abstract presents a concise overview of smart monitoring and control systems for aquaculture water treatment. It highlights the critical safety and productivity challenges faced by aquaculture due to fluctuations in essential water quality parameters such as temperature, pH, dissolved oxygen, and ammonia. Traditional water quality monitoring m...
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Research Article
An FM Broadcast IoT System for Enhancing Highway Safety
Issue:
Volume 13, Issue 2, December 2025
Pages:
33-45
Received:
25 August 2025
Accepted:
10 September 2025
Published:
14 October 2025
DOI:
10.11648/j.ijssn.20251302.12
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Views:
Abstract: Land travel on highways in developing countries, such as Cameroon, faces significant safety challenges due to factors like natural disasters, poor road networks, low-quality vehicles, error-prone drivers, and negligent pedestrians, with government investments showing only minor improvements in reducing road accidents. This paper proposes an Internet of Things (IoT) based FM broadcast system to enhance highway safety by providing real-time and timely guides to drivers. The proposed system comprises three main units: a Roadside Unit (RSU), an Onboard Unit (OBU), and a Control Centre (CC). The RSU is an IoT-based smart unit built around a Raspberry Pi 4 Model B, equipped with environmental sensors (DHT11 for temperature/humidity, ROBODO 130008 for rain) and internet connectivity. It integrates a locally designed 5W Phase Locked Loop (PLL) FM transmitter, set to a test frequency of 100.8 MHz, with a broadcast radius of 10 km. Python code on the RSU utilizes APIs like OpenWeatherMap and Google Suite to gather real-time weather forecasts, environmental data, traffic conditions (estimated arrival times, delays), and information on nearby places (parking, gas stations, lodging). It also dynamically suggests speed limits based on real-time weather and generates audio warnings for adverse conditions and road events. The system primarily uses an audio-only broadcast to minimize driver distraction. The OBU functions as a specialized receiver, consisting of a Raspberry Pi 4 Model B with an RTL-SDR dongle that demodulates and outputs FM audio to speakers, with GNU Radio software processing the signals. A remote-Control Centre manages and configures RSUs securely via SSH, enhancing operational efficiency. Experimental results confirm the system's effectiveness. The locally designed FM transmitter demonstrated robust performance with a total RF gain of 43 dB and stable 5W output power, along with excellent frequency stability (±50 ppm crystal oscillator, -90 dBc/Hz VCO phase noise). Performance indicators like Signal-to-Noise Ratio (SNR), Modulation Error Rate (MER), and power spectrum were analysed. SNR showed an inverse relationship with distance, dropping to -40.36 dB at 5000m, which is acceptable for highway radio quality, and tracked closely with a commercial transmitter. MER analysis indicated proper functioning of the transmitter-receiver pair, as demodulated signals exhibited tightly clustered constellation points, implying high SNR and better audio quality. Furthermore, the power spectrum showed minimal variation between original and received audio signals, with an improved gain post-modulation, ensuring clear audio output. This comprehensive system provides a robust and cost-effective solution for real-time highway advisories in developing countries.
Abstract: Land travel on highways in developing countries, such as Cameroon, faces significant safety challenges due to factors like natural disasters, poor road networks, low-quality vehicles, error-prone drivers, and negligent pedestrians, with government investments showing only minor improvements in reducing road accidents. This paper proposes an Interne...
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