Page 63 - IMDR Journal 2025

Research Article
dialogue on sustainable water management and guide future administration of irrigation systems. Studies showcase that
developments in smart irrigation technologies. cloud-centric platforms expedite real-time data
accumulation, historical trend scrutiny, and automated
decision-making predicated on sensor inputs.
OBJECTIVES
- Research underscores that cloud-integrated systems
1. Look at how well IoT-based watering systems work in empower farmers to optimize water consumption and
helping plants get the right amount of water. Focus on how anticipate irrigation requisites based on weather conditions
these systems can be used to make sure water is used in the and soil parameters.
best possible way while also supporting long-term
3. AI-Integrated Irrigation Control Systems by Li, X., &
sustainability goals.
Wang, Y. (2021)
2. Review the existing studies and publications that talk - Artificial intelligence (AI) is progressively harnessed to
about automated irrigation technologies that use the Internet automate irrigation scheduling. Studies indicate that AI-
of Things. Clearly explain what benefits these technologies driven models scrutinize sensor data, weather predictions,
offer and also discuss the drawbacks or challenges that come and crop water demands to fine-tune watering schedules.
with using them.
- Machine learning techniques like neural networks and
3. Identify the gaps that still exist in the research on decision trees bolster predictive analytics, thereby refining
intelligent irrigation systems that rely on IoT. Highlight the irrigation efficacy and mitigating manual interventions.
areas that need more study so these smart systems can be
improved and made even more effective in the future. 4. Low-Power Wireless Networks in Smart Irrigation by
Thompson, D., & Lee, J. (2018)
4.Do a comparative and quantitative analysis of the different
types of IoT-based irrigation technologies. Look at how they - Wireless communication technologies such as Zigbee,
perform in terms of conserving water, saving energy, LoRa, and Bluetooth Low Energy (BLE) facilitate long-
reducing costs, and being flexible enough to adapt to range, low-power data transmission between sensors and
different needs and environments. controllers.
5. Find and suggest opportunities for improving smart - Research suggests that LoRaWAN-based irrigation
irrigation systems. Explore ideas for new features, better networks are exceptionally advantageous for large-scale
designs, or technological innovations that can make these agricultural settings owing to their energy efficiency and
systems work even better and meet the needs of different expansive coverage.
users. 5. Machine Learning for Predictive Watering Models by
6. Share useful information and insights that can help Wang, H., & Zhang, L. (2021)
support more sustainable ways of managing water. Focus on - Studies accentuate that predictive models leveraging
ideas that can be applied both in large-scale agriculture and machine learning algorithms heighten water conservation
in smaller urban garden settings to promote better water use by dynamically adjusting irrigation schedules based on
and conservation practices. climatic patterns and soil moisture levels.
- Research implies that AI-enhanced models can curtail
water wastage by assimilating past data and adapting
LITERATURE REVIEW
irrigation patterns accordingly.
The emergence of IoT-based smart irrigation systems has 6. Solar-Powered IoT Irrigation Solutions by Kim, J., &
captured considerable attention in recent times, with Park, S. (2019)
numerous research endeavors delving into various facets of
these technologies. This section delves into pivotal studies, - Solar energy is progressively integrated into IoT irrigation
shedding light on technological progressions, system systems to bolster sustainability. Research indicates that
frameworks, and their implications in fostering sustainable solar-powered irrigation setups diminish reliance on
water management. traditional electricity, rendering them ideal for remote and
off-grid locales.
1. Smart Irrigation Systems Utilizing Soil Moisture
Sensors by Smith, J., & Brown, R. (2019) - Studies also underscore that solar energy harvesting
mechanisms can be conjoined with battery storage solutions
- Soil moisture sensors play a pivotal role in refining
irrigation practices by ensuring water is dispensed only as to ensure uninterrupted operation.
necessary. Studies indicate that the utilization of capacitive 7. Blockchain for Water Resource Management by
and resistive soil moisture sensors can enhance Kumar, S., & Verma, R. (2022)
measurement precision, thereby augmenting irrigation - Blockchain technology is emerging as a prospective
efficiency. solution for decentralized water management within smart
- Research outcomes propose that amalgamating real-time irrigation systems.
soil moisture data with automated irrigation controllers - Studies advocate that blockchain-based smart contracts
substantially curtails water wastage. can automate water allocation, guaranteeing transparency
2. Cloud-Based IoT Architecture for Precision and accountability in resource utilization.
Agriculture by Patel, M., & Kumar, S. (2020) 8. Automated Hydroponic Watering Systems by Das, M.,
- Cloud computing facilitates remote surveillance and & Gupta, S. (2020)

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