ABSTRACT
Water scarcity and inefficient water distribution have become major challenges in rapidly growing urban environments. Traditional water management systems suffer from leakage, unequal distribution, delayed fault detection, and lack of real-time monitoring. This paper proposes a Smart Water Distribution Monitoring System that integrates Internet of Things (IoT) devices, cloud computing, artificial intelligence (AI), and wireless sensor networks to enhance water distribution efficiency. The proposed system continuously monitors water quality, flow rate, pressure levels, reservoir status, and consumer usage patterns through smart sensors installed at strategic locations. The collected data is transmitted to a cloud platform where machine learning algorithms analyze consumption trends, predict demand, and identify abnormal conditions such as leakage, contamination, and unauthorized usage. Automated control valves regulate water distribution based on demand forecasting and resource availability. The system improves water conservation, reduces operational costs, minimizes water losses, and ensures equitable distribution. Experimental analysis demonstrates significant improvements in monitoring accuracy, leak detection efficiency, and water utilization compared to conventional systems. The proposed framework contributes toward the development of sustainable smart cities and intelligent water resource management.
Keywords: Internet of Things (IoT), Smart Water Management, Cloud Computing, Artificial Intelligence, Water Distribution Network, Leak Detection, Smart Cities, Wireless Sensor Networks.
Dr B Rajanna, Bandari Rakesh, Kalala Surendar· International Scientific Jou...· 0 citations
Abstract
The increasing demand for energy-efficient digital systems in portable, embedded, and Internet of Things (IoT) applications has made low-power design an important objective in modern VLSI and FPGA-based systems. This work presents the design and FPGA implementation of a Low-Power Leakage-Aware Digital Processing Unit (DPU) using Verilog HDL. The proposed architecture incorporates leakage-aware design techniques such as enable-controlled functional blocks, clock-enable based operation, and selective activation of processing modules to minimize unnecessary switching activity and reduce overall power consumption. The Digital Processing Unit performs fundamental arithmetic and logical operations while dynamically controlling inactive circuit sections to improve energy efficiency. The design is modeled at the Register Transfer Level (RTL), simulated for functional verification, and synthesized using the Xilinx Vivado design environment. Performance evaluation is carried out in terms of power consumption, resource utilization, timing characteristics, and operating frequency. Experimental results demonstrate that the proposed leakage-aware architecture achieves lower power dissipation compared to conventional processing units while maintaining reliable computational performance. The combination of low-power operation, efficient hardware utilization, and FPGA-based implementation makes the proposed design suitable for battery-operated devices, edge computing systems, and real-time embedded applications.
Keywords: Low-Power Digital Processing Unit (DPU), Leakage-Aware Design, FPGA Implementation, Verilog HDL, Energy-Efficient VLSI.
Embadi Thirumala, Dr B Rajanna· International Scientific Jou...· 0 citations
