Author:
Mallikarjuna Reddy Dr.V.,Hamsalekha S.
Abstract
In the present era, water scarcity is the biggest problem. In Construction potable water is required for mixing and curing of concrete. The curing process is required for 28 days. So the water requirement in the construction field for curing purposes is very large. Due to various reasons, potable water availability is decreasing day by day. So it is required to spend a considerable amount on the procurement of water. To control the wastage of water for curing it is necessary to use water in a controlled manner by adopting advanced technology. It is known as a smart concrete curing system. The smart concrete curing system is developed to create an automatic curing mechanism to supply water for curing depending on the availability of moisture in the concrete and surrounding temperature using moisture sensor. The system will be connected to the internet using Wi-Fi. The current moisture content level of the concrete structure and the pump status will be pushed to the cloud. A mobile app will access this data from the cloud. So that the curing process monitoring can be done remotely. Results shown that strength of the cube with smart concrete curing system is more than the strength of the cube with immersion curing.
Reference16 articles.
1. cameras Jaoquin, Sanchez Trinidad, Antonio Juan, Gomez-galan, Hector Cifuentes and Ramon Gonzalez, “Compact embedded wireless sensor-based monitoring of concrete curing”, Multidisciplinary digital publishing Institute, MDPI, (2018).
2. Kanchan Ambekar and Gandhare K.U “Developing a new curing technique-’Drip curing’”, International Journal for Research in applied science and Engineering technology, IJRASET, Volume 05, Issue 07, (2017).
3. Nayak P., Devulapalli A. A Fuzzy Logic-Based Clustering Algorithm for WSN to Extend the Network Lifetime. IEEE Sensors Journal, 16 (1), art. no. 7222367, pp. 137-144. Cited 213 times. (2016).
4. Nayak P., Vathasavai B. Energy Efficient Clustering Algorithm for Multi-Hop Wireless Sensor Network Using Type-2 Fuzzy Logic. IEEE Sensors Journal, 17 (14), art. No. 7938335, pp. 4492-4499. Cited 68 times. (2017).
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