RainRoof: Automated Shared Rainwater Harvesting Prediction

Gaurav, Vipul; Vinod, Vishal; Singh, Sanyam Kumar; Sharma, Tushar; Pradyumna, K. R.; Choudhary, Sudhanshu

doi:10.1007/978-981-15-8677-4_9

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…Due to the complexity of the system's viability, numerous manual inspections are required. The suggested work [90] supports this process by combining computer vision-based solutions that automate the entire process by implementing rooftop picture segmentation, depth estimation, rainfall forecast and optimal tank placement using machine learning and deep learning algorithms. A rolling forecasting model based on seasonal autoregressive moving averages (SARIMA) is used to predict rainfall.…”

Section: Recent Trends Of Deep Learning On Rainwater Managementmentioning

confidence: 99%

“…These processes can be handled by deep learning techniques with a desired power of GPU (Graphical Processing Units) and software. Various application with significant parameters are listed in Table 2 [82] Application of multi-agent deep enforcement learning (MADRL) with LCA optimization in waste water treatment plants [83] FOG estimation on waste water pumping stations [90] Seasonal auto regressive moving average (SARIMA) with R-CNN enhanced with canny edge algorithm with contour mapping [92] Smart irrigation system based on computer vision and deep learning. Alex Net, Google Net, Res Net, VGG16 and Squeeze net are the deep learning applications used.…”

Section: Recent Trends In Irrigation Control Using Deep Learningmentioning

confidence: 99%

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Smart Water Resource Management Using Artificial Intelligence—A Review

Somayaji

Nallakaruppan²,

Chengoden³

et al. 2022

Sustainability

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Water management is one of the crucial topics discussed in most of the international forums. Water harvesting and recycling are the major requirements to meet the global upcoming demand of the water crisis, which is prevalent. To achieve this, we need more emphasis on water management techniques that are applied across various categories of the applications. Keeping in mind the population density index, there is a dire need to implement intelligent water management mechanisms for effective distribution, conservation and to maintain the water quality standards for various purposes. The prescribed work discusses about few major areas of applications that are required for efficient water management. Those are recent trends in wastewater recycle, water distribution, rainwater harvesting and irrigation management using various Artificial Intelligence (AI) models. The data acquired for these applications are purely unique and also differs by type. Hence, there is a dire need to use a model or algorithm that can be applied to provide solutions across all these applications. Artificial Intelligence (AI) and Deep Learning (DL) techniques along with the Internet of things (IoT) framework can facilitate in designing a smart water management system for sustainable water usage from natural resources. This work surveys various water management techniques and the use of AI/DL along with the IoT network and case studies, sample statistical analysis to develop an efficient water management framework.

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Section: Recent Trends Of Deep Learning On Rainwater Managementmentioning

confidence: 99%