IoT-Enabled Smart Aquarium System for Automated Feeding and Real-time Monitoring | Chapter 4 | Intelligent IoT Systems: From Research to Real-World Solutions

 

There are significant requirements for environmental monitoring and fish feeding logs when managing an aquarium, which can also be tedious and error-prone for the caregiver/technician. The rapid adoption of Internet of Things (IoT) technologies opens up exciting new opportunities for aquarium management by automating tasks that will allow the environment to remain stable for the aquatic life. This chapter discusses the design and evaluation of a Smart Aquarium System that can automate fish feeding and monitor temperature, pH, turbidity, and water level, as well as real-time connectivity via the cloud. An ESP32-CAM module was also integrated into the system, which transmits live video and images, so fish and how the system is functioning can be observed remotely. The Smart Aquarium system was tested under various operating conditions to evaluate accuracy, responsiveness, and reliability. The results showed it had a feeding accuracy of 96.4%, temperature maintained to a range of ±0.5 °C, pH was reliably detected in the 6.0–8.0 range, turbidity results were reported in NTU units, and the water level stabilised within a range of ±1 cm, respectively. Cloud-based data transfer was accomplished with an average latency of less than 200 ms, which supported effective real-time cloud and local visualisation and control. Safety procedures, such as dry-run prevention for a pump and fault-detection for sensors, were established to enhance reliability. Overall, the results suggest that IoT-based smart aquariums indicate a reduction in manual workload, improve user management of aquatic health and potentially be a low-cost tool for users, including aquaculture operators and hobbyists.

 

 

Author(s) Details

 

Hanamant R Jakaraddi
Department of MCA, Acharya Institute of Technology, Bangalore- 560107, India.

 

Anurag O
Department of MCA, Acharya Institute of Technology, Bangalore- 560107, India.

 

Vivek R Venkatesh
Department of Computer Applications, Acharya Institute of Graduate Studies, Bangalore-560107, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/mono/978-93-88417-94-5/CH4

IOT-Based Smart Energy Management System for Real-Time Monitoring and Automation | Chapter 2 | Intelligent IoT Systems: From Research to Real-World Solutions

 

In present days, energy consumption is becoming a major concern for individuals, businesses, and agriculture. Inefficient energy consumption contributes to environmental degradation by raising electricity bills and increasing reliance on non-renewable resources. This approach gives a design and implements an IoT-based Smart Energy Management System for real-time monitoring, predictive automation, and cloud-based control of electrical appliances in smart homes. The system was created using various sensors to track voltage, current, temperature, occupancy and light. Real-time automation was obtained using relay modules and a servo motor for curtain automation. Firebase Realtime Database was utilised for cloud storage, control, and predictive data retrieval. Energy consumption was calculated in kilowatt-hours based on voltage and current values. Manual, schedule-based, and predictive override were implemented. The system effectively monitored energy consumption and reduced power levels by 18%. It automatically shut down equipment when idle or in accordance with pre-scheduled occupancy estimates. The system responded in real-time to sensor inputs and user-scheduled events. Power telemetry and daily logging were always synchronised with Firebase to enable smooth cloud updates and user interaction. The proposed system offers a safe, scalable, and intelligent home energy management system for the future through the use of IoT sensors and cloud technology to enable automation, predictive control, safety, and future-proof compatibility with new smart grid infrastructure for improved sustainability and operational efficiency.

 

 

Author(s) Details

Hanamant R Jakaraddi
Department of MCA, Acharya Institute of Technology, Bangalore-560107, India.

 

Amarnath C K
Department of MCA, Acharya Institute of Technology, Bangalore-560107, India.

 

Ranjana K K
Department of Computer Applications, Acharya Institute of Graduate Studies, Bangalore-560107, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/mono/978-93-88417-94-5/CH2