TY - CHAP
T1 - IoT-Based Nutrient Monitorization in Hydroponics Using Bioinformatics Tools
AU - Sharma, Manvi
AU - Surada, Shrutika
AU - Sirkeck, Vinayak
AU - Pal, Tarun
AU - Kumari, Chandresh
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
PY - 2026/1/1
Y1 - 2026/1/1
N2 - Hydroponics is a successful effort in contemporary agriculture for more efficient crop production in a much smaller area. The incorporation of the Internet of Things (IoT) enhanced the accessibility to address various issues, and with much more precision, such a revolutionized pattern of parameter monitoring leads to the optimization of nutrients and environmental conditions in real time, thereby increasing the yield with sustainable resource management. This chapter has included the complementarity among IoT, bioinformatics, and hydroponics systems in agriculture, mainly focusing on the real-time data collection and analysis for quicker action and advanced preventive measures, and efficient management. Sensor calibration, data integration, and analysis in association with precise computation techniques help in the process of analysis and interpretation of results. All these techniques and software put together into action have harnessed the power of the computational world with agriculture for nutrient profiling, in an attempt to lead the path of resilient and resource-efficient agriculture and encounter the challenges of global food security.
AB - Hydroponics is a successful effort in contemporary agriculture for more efficient crop production in a much smaller area. The incorporation of the Internet of Things (IoT) enhanced the accessibility to address various issues, and with much more precision, such a revolutionized pattern of parameter monitoring leads to the optimization of nutrients and environmental conditions in real time, thereby increasing the yield with sustainable resource management. This chapter has included the complementarity among IoT, bioinformatics, and hydroponics systems in agriculture, mainly focusing on the real-time data collection and analysis for quicker action and advanced preventive measures, and efficient management. Sensor calibration, data integration, and analysis in association with precise computation techniques help in the process of analysis and interpretation of results. All these techniques and software put together into action have harnessed the power of the computational world with agriculture for nutrient profiling, in an attempt to lead the path of resilient and resource-efficient agriculture and encounter the challenges of global food security.
KW - AI automation
KW - Nutrient Film Technique
KW - QTL mapping
KW - Regression tree
KW - Wireless communication
UR - https://www.scopus.com/pages/publications/105029423160
U2 - 10.1007/978-981-95-3963-5_14
DO - 10.1007/978-981-95-3963-5_14
M3 - Chapter
AN - SCOPUS:105029423160
T3 - Smart Agriculture (Singapore)
SP - 263
EP - 290
BT - Smart Agriculture (Singapore)
PB - Springer
ER -