The fact that the world population has created exponentially great food demand on the sea, along with the fact that the wild fish stocks have been recorded to be depleted, has placed aquaculture as an unavoidable element of the modern food system. Nevertheless, the effective output of fish farming activities and environmental sustainability is highly conditional upon the provision of appropriate water quality conditions during the production cycle. The paper is a data-driven case study exploring the effects of Industrial Internet of Things (IIoT) sensor-based water quality monitoring on the health outcome, growth performance, and disease incidence in the aquaculture operations of pond based in Monteria, Colombia..........

[1]. Food and Agriculture Organization of the United Nations. (2022). The State of World Fisheries and Aquaculture 2022: Towards Blue Transformation. FAO. Rome.
[2]. Boyd, C. E., D'Abramo, L. R., Glencross, B. D., Huyben, D. C., Juarez, L. M., Lockwood, G. S., & Valenti, W. C. (2020). Achieving sustainable aquaculture: Historical and current perspectives and future needs and challenges. Journal of the World Aquaculture Society, 51(3), 578–633.
[3]. Timmons, M. B., & Ebeling, J. M. (2013). Recirculating Aquaculture (3rd ed.). Ithaca Publishing Company.
[4]. Wedemeyer, G. A. (1996). Physiology of Fish in Intensive Culture Systems. Chapman and Hall, New York.
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Traditional water management practices rely on static hydraulic models, manual inspections, and reactive maintenance, making them increasingly inadequate in coping with evolving challenges from global urbanization, climate variability, resource limitations, and infrastructure ageing.This study investigates the integration of Artificial Intelligence (AI), Machine Learning (ML), and IoT technologies to optimize urban water systems in real time through proactive leak detection, adaptive demand forecasting, and autonomous quality monitoring.The research presents a framework leveraging predictive analytics, smart sensing networks, and IoT-enabled infrastructure.........

[1]. L. Abdulameer, M. S. Al-Khafaji, A. T. Al-Awadi, et al., "Artificial intelligence in climate-resilient water management: A systematic review of applications, challenges, and future directions," Water Conservation Science and Engineering, vol. 10, no. 1, p. 44, 2025.
[2]. A. Al-Fuqahaet al., "The role of IoT in smart water networks," 2023.
[3]. A. Malek and M. Alimardani, "Enhancing SCADA with AI: A hybrid control approach for smart water utilities," Automation in Construction, vol. 98, pp. 108–116, 2019.
[4]. P. Singh, A. Mishra, and R. Jain, "Artificial intelligence in water resource management: Applications and future perspectives," Sustainable Water Resources Management, vol. 6, no. 4, p. 78, 2020.
[5]. M. Hamouda, M. Elshafei, and M. Mahmoud, "Machine learning applications in water distribution networks: Leak detection and demand management," Journal of Hydroinformatics, vol. 24, no. 3, pp. 567–583, 2022

Locally fabricated stationary grain threshers are widely used by smallholder farmers in Nigeria; however, the internal biomechanical loading imposed on operators during machine feeding tasks has received limited quantitative investigation. This study developed a biomechanical strain model linking lifting parameters, joint kinematics, and operational productivity to internal spinal loading during operation of two engine-powered stationary threshers. Thirteen experienced operators performed standardized threshing tasks using Machine 1 (M1: feed height 92 cm; capacity 3000 kg·h⁻¹) and Machine 2 (M2: feed height 161.5 cm; capacity 6500 kg·h⁻¹). Anthropometric characteristics, lifting frequency, load mass per lift, and trunk and upper-limb joint angles were recorded........

[1]. Binswanger-Mkhize, H. P. (2017). Agricultural mechanization in Sub-Saharan Africa: A review of evidence. World Bank Research Observer, 32(1), 1–35. [2]. Chaffin, D. B., Andersson, G. B. J., and Martin, B. J. (2006). Occupational biomechanics (4th ed.). Wiley. [3]. Diao, X., Takeshima, H., and Zhang, X. (2020). An evolving paradigm of agricultural mechanization development: How much can Africa learn from Asia? Global Food Security, 26, 100427. [4]. Food and Agriculture Organization. (2018). Sustainable agricultural mechanization: A framework for Africa. FAO.
[5]. Hignett, S., and McAtamney, L. (2000). Rapid Entire Body Assessment (REBA). Applied Ergonomics, 31(2), 201–205.

Moving goods by commercial truck fleets matters a lot in shipping products across regions. Still, problems popup-driversgettired,losefocusbehindthewheel,fuelgoesmissing,packagesvanish,andtoughweather adds risk. Older tracking toolslean heavily on GPS signals plus remote computing, costing too much while slowingdownupdates.Thisstudyintroducesabudget-friendlysetupusingmanysmallsensorstowatchboth..........

[1] A.Mohamed,K.Singh,andM.Patel,"Real-timedriverdrowsinessdetectionusingdeepfaciallandmark analysis,"IEEETransactionsonIntelligentTransportationSystems,vol.21,no.5,pp.2150–2159,May 2020.
[2] Y. Zhao, H. Liu, and J. Chen, "Head pose estimation for driver monitoring using low-cost inertial sensors," IEEE Sensors Journal, vol. 19, no. 12, pp. 4567–4575, June 2019.
[3] V. Ramachandran and P. Krishnamurthy, "Driver fatigue detection using PERCLOS and EEG-based features," in Proceedings of the IEEE International Conference on Signal Processing and Communication, Bangalore, India, 2021, pp. 112–117.
[4] S. Patel, A. Jain, and R. Verma, "Accelerometer-based driver behaviour classification for fleet monitoring,"InternationalJournalofEngineeringResearchandTechnology,vol.9,no.4,pp.112–118, April 2020.
[5] InvenSenseInc., "MPU-6000 and MPU-6050 Product Specification, Revision 3.4," TDK InvenSense, San Jose, CA, USA, 2013.

Drying of grains into various feed-stocks is needed for one or several of the following reasons: need for easy-to-handle free-flowing solids, preservation and storage, reduction in cost of transportation, achieving desired quality of products. Therefore, it is necessary that these grains are properly dried and stored to ensureavailability. The main objectives of this study were to improve on the existing design of electric paddle grain dryer as follows:(1). Replacement of the analog thermometer whose measurement variation could not be established with digital thermometer for better efficiency........

[1]. Adzimah, K.S and Seckley, E {2009}: "Improvement on the Design of a Cabinet Grain Dryer", America Journal of Engineering and Applied Science 2 (1). Pg. 217 - 228. ISSN 1941 – 7020.
[2]. Khurmi,R.S.K. and Gupta J.K (2012). A textbook of Mechanic design, New Delhi Eurasia publishing house.
[3]. Khurmi, R. S Gupta, (2014): Machine Design: shaft, v-belt and rope, s chand and co.Ltd, New Delhi. Pp 465-498.
[4]. Mujumdar, A.S (2006): "Principles Classification and Selection of Dryers", Handbook of Industrial Drying, Ed; Mujumdar, A.S; Taylor and Francis Group, Part I, Chapter 1, Pg. 29 – 58.
[5]. Madhlopa A, Jones S A, and KalengaSaka J. D (2002): "A Solar Air Heater with composite Absorber Systems for Food Dehydration. Renewable Energy", 27; 27 – 37.

The primary objective of this project is to investigate and demonstrate the efficacy of seismic isolation systems in protecting civil infrastructure from the devastating effects of earthquakes. Natural disasters like earthquakes pose a significant threat to the built environment, often leading to catastrophic structural failures and the loss of human life due to improper design against dynamic lateral forces. This project focuses on the transition from traditional "strength-based" design to a modern "displacement-based" approach, emphasizing the preservation of both the structure and its internal contents..........

........

Women's health has long faced unique challenges due to historical underrepresentation in research and limited access to gender-specific healthcare solutions. This paper explores how biotechnology is reshaping the landscape of women's health through advancements in diagnostics, therapeutics, and personalized medicine. By examining key developmentsfrom reproductive technologies and genomic medicine to chronic disease management and mental health innovationsthis study highlights biotechnology's transformative role in promoting wellbeing and empowerment. Integrating historical perspectives, recent research, and real-world applications, it underscores how biotechnological innovations can bridge gender disparities in healthcare and ensure equitable access to cutting-edge medical care for women worldwide.

[1]. Brown, T., Wilson, A., Patel, S., & Khan, R. (2024). Data privacy in genomic medicine: Protecting women's genetic information. Journal of Medical Ethics, 50(2), 123–135.
[2]. Chen, X., Li, Y., Zhao, L., & Wang, M. (2024). Advances in non-invasive prenatal testing: Detecting fetal sex chromosome aneuploidies. Prenatal Diagnosis, 44(3), 210–220.
[3]. Funding research on women's health.(2024, October).Nature, 623, 455. https://doi.org/10.1038/d41586-024-00253-7
[4]. Garcia, M., Lopez, D., Hernandez, C., & Park, S. (2024). Wearable biotech devices for mental health monitoring: A new frontier in women's wellbeing. Journal of Medical Innovation, 15(4), 112–125.
[5]. Grace, B. (2025). Digital health technologies to transform women's health.BMJ, 391, 085682. https://doi.org/10.1136/bmj.085682

The Smart Energy Meter Adaptive Load Control Monitoring System is an advanced solution designed to monitor, analyse, and control electrical energy consumption in real time. This system utilizes an ESP32 microcontroller integrated with voltage and current sensors (ZMPT101B and ZMCT103C) to measure electrical parameters accurately. The collected data is displayed on a 16×4 LCD and simultaneously stored in an SD card module for future analysis. The system also incorporates an RTC DS3231 module to maintain precise time records for energy usage logging. Additionally, the system enables adaptive load control using relays connected........

[1]. K. Sharma, R. Patel "AI-Based Smart Energy Meter for Real-Time Power Monitoring" International Journal of Smart Grid Technology, 2025
[2]. S. Kumar, P. Singh. "Cloud-Integrated IoT Smart Meter for Energy Management" IEEE Access, 2025
[3]. A. Verma, N. Gupta "IoT Enabled Smart Energy Meter for Efficient Power Management" Journal of Electrical and Computer Engineering, 2024
[4]. M. Reddy, S. Rao "Smart Metering System for Energy Monitoring Using Cloud Platform" IEEE International Conference on Smart Energy Systems, 2023
[5]. R. Karthik, V. Kumar "IoT-Based Smart Energy Meter with Real-Time Monitoring" International Journal of Advanced Research in Electrical Engineering, 2021

The aim of our research is to study the Bianchi type-I cosmological model as a coupling between a cosmic string and an electromagnetic field in Bimetric theory. This led to the existence of the "False Vacuum Model" of the universe (𝜌=𝜆=0) being filled with "Vacuum energy". The constant value of the Hubble parameter(𝐻) indicates the expansion of the universe at a constant rate. i.e. 70𝑘𝑚𝑠−1/𝑀𝑝𝑐=𝐻0which is a result of the constant value of scalar expansion(𝜃). The expansion is found to be uneven from the constant value of the anisotropy parameter(𝐴).

[1]. N. Rosen, A bi-metric theory of gravitation, Gen. Relativ. Gravit. 4, 435–447 (1973).DOI: 10.1007/BF01215403.
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[3]. C. B. Collins, E. N. Glass, and D. A. Wilkinson, Exact spatially homogeneous cosmologies, Gen. Relativ. Gravit. 12, 805–823 (1980). DOI: 10.1007/BF00763057.
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The use of the internet has increased rapidly in recent years, and many users spend a large amount of time on websites such as social media, gaming, and streaming platforms. Sometimes these websites become distractions and may also expose users to harmful or unwanted content. To solve this problem, a software firewall system has been developed using Python programming language. The main purpose of this project is to block selected websites on a computer system and control internet access. The system works by modifying the hosts file of the operating system so that when a user tries to open a blocked website, the browser cannot access it...........

[1] W. Stallings, Network Security Essentials: Applications and Standards, 6th ed. Boston, MA, USA: Pearson, 2017.
[2] J. F. Kurose and K. W. Ross, Computer Networking: A Top-Down Approach, 7th ed. Boston, MA, USA: Pearson Education, 2017.
[3] Python Software Foundation, Python Documentation. Available:https://www.python.org
[4] Tkinter Documentation, "Python Graphical User Interface Programming." Available:https://docs.python.org
[5] Microsoft, "Windows Hosts File Documentation." Available:https://learn.microsoft.com

This paper seeks on how to supply electricity to Ihuaba community in Rivers State Nigeria, which currently lacks access to grid electricity, thereby limiting healthcare service delivery, constraining educational development, reducing economic productivity and hindering overall socio-economic growth. The absence of stable power supply has forced residents to rely on costly and environmentally harmful alternatives such as diesel generators and kerosene-based systems. In response to these challenges, this study evaluates the technical, economic, and electrical network viability of deploying an off-grid solar photovoltaic (PV) mini-grid system tailored specifically.........

[1]. Akinboro, T., Lu, J. C. V. X., & Guerrero, J. M. (2016). DC microgrids—Part I: A review of control strategies and stabilization techniques. IEEE Transactions on Power Electronics, 31(7), 4876–4891. https://doi.org/10.1109/TPEL.2015.2478857
[2]. Cherukupalli, N. (2018). Mokhtari, H., & Blaabjerg, F. (2017). Hierarchical power sharing control in DC microgrids. In Microgrid (pp. 63–100). Elsevier. https://doi.org/10.1016/B978-0-12-803904-8.00003-2
[3]. Dahlke, Siavashi, E. M. (2018). PV-STATCOM: A new smart inverter for voltage control in distribution systems. IEEE Transactions on Sustainable Energy, 9(4), 1681–1691.
[4]. Farrokhabadi, M., Cañizares, C. A., Simpson-Porco, J. W., Nasr, E., Fan, L., Mendoza-Araya, P. A., Tonkoski, R., Tamrakar, U., Hatziargyriou, N., Lagos, D., et al. (2020). Microgrid stability definitions, analysis, and examples. IEEE Transactions on Power Systems, 35(1), 13–29. https://doi.org/[insert DOI]
[5]. Kawabe, K., Ota, Y., Yokoyama, A., & Tanaka, K. (2016). Novel dynamic voltage support capability of photovoltaic systems for improvement of short-term voltage stability in power systems. IEEE Transactions on Power Systems, 32(3), 1796–1804. https://doi.org/10.1109/TPWRS.2016.2616439

Integrating Electric Vehicles (EVs) into home-based microgrid systems presents significant opportunities for sustainable energy transition, particularly in sub-Saharan regions where renewable energy resource diversity remains underexplored. This study proposes a home-based microgrid EV charging architecture incorporating an adaptive Renewable Energy (RE) source selection mechanism and evaluates for the Rumuagholu Metropolis in Obio/Akpor Local Government Area, Rivers State, Nigeria. A Simple Logical Analysis (SLA) algorithm is developed to determine the most power-viable RE source - solar photovoltaic (PV) or biogas, on an hourly...........

[1]. Ayodele, T. R., Ogunjuyigbe, A. S. O., Akpeji, K. O., & Akinola, O. O. (2017). Prioritized rule based load management technique
for residential building powered by PV/battery system. Engineering science and technology, an international journal, 20(3), 859- 873.
https://doi.org/10.1016/j.jestch.2017.04.003
[2]. Celik, B., Roche, R., Bouquain, D., & Miraoui, A. (2017). Decentralized neighborhood energy management with coordinated smart home energy sharing. IEEE Transactions on Smart Grid, 9(6), 6387-6397. https://doi.org/10.1109/tsg.2017.2710358
[3]. Erdinc, O., Paterakis, N. G., Pappi, I. N., Bakirtzis, A. G., & Catalão, J. P. (2015). A new perspective for sizing of distributed
generation and energy storage for smart households under demand response. Applied Energy, 143, 26-37. https://doi.org/10.1016/j.apenergy.2015.01.025
[4]. Hemmati, M. (2017). A Sustainable Transition to Renewable Energy Resources in Oil Producing Countries: A Case Study of
Iran. Journal of Solar Energy Research, 24, 249-272. https://jser.ut.ac.ir/article_64917_130e3847388701b782bb97f4a16b6644.pdf
[5]. Iwafune, Y., Ikegami, T., da Silva Fonseca Jr, J. G., Oozeki, T., & Ogimoto, K. (2015). Cooperative home energy management
using batteries for a photovoltaic system considering the diversity of households. Energy conversion and management, 96, 322-329.
https://doi.org/10.1016/j.enconman.2015.02.083

Classical time complexity analysis models algorithmic cost through asymptotic growth of arithmetic operations with respect to input size, abstracting away hardware-specific factors such as memory hierarchy and communication latency. Contemporary artificial-intelligence workloads frequently involve large-scale distributed training across heterogeneous accelerators, where runtime is influenced not only by arithmetic operations but also by communication, memory access, and energy consumption. This paper re-examines algorithmic efficiency under these large-scale conditions and proposes a multi-dimensional framework for time complexity that integrates five interacting factors: computational, communication, memory, energy, and empirical performance metrics............

[1] Kitaev, N.; Kaiser, Ł.; Levskaya, A. Reformer: The Efficient Transformer. arXiv preprint arXiv:2001.04451, 2020.
[2] H. K. Kushwaha, "Time Complexity in the Age of Big Data and Artificial Intelligence: A Multi-Dimensional Framework," Zenodo,
2026. doi:10.5281/zenodo.18171274.
[3] Tay, Y.; Dehghani, M.; Bahri, D.; Metzler, D. Efficient Transformers: A Survey. ACM Computing Surveys, 2022, 55(6), 1–28.
[4] Song, J.; Meng, C.; Ermon, S. Denoising Diffusion Implicit Models (DDIM). arXiv preprint arXiv:2010.02502, 2020.
[5] Yang, S.; Zhang, X.; Li, Z. Diffusion Models: A Comprehensive Survey. ACM Transactions on Multimedia Computing,
Communications, and Applications (TOMM), 2023, 19(3), 1–33.

This paper characterizes the depositional sequence and paleoenvironmental evolution of the OBJ Field in the Niger Delta, utilizing a total of three well logs (OBJ 1, 2, and 3) obtained from the Nigerian Agip Oil Company (NAOC). Integration of gamma ray log motifs reveals a vertical succession typically the Agbada Formation, transitioning from basal progradational delta front shales into a 25m thick, blocky reservoir sand in OBJ-2. This interval is significant tohigh energy distributary channel or shoreface depocenter within a highstand or regressive systems tract...........

[1]. Aikulola, U. O; Olotu, S. O; Yamas, I. (2010). Investigating Fault Shadows in the Niger Delta. The Leading Edge, 29(1), 16-22. DOI: https://doi.org/10.1190/1.3284048
[2]. Chiazor, F. I; Ugwueze, C. U. (2020). Sequence stratigraphy and petrophysical evaluation of Miocene sediments in the Eastern Niger Delta Basin, Nigeria. International Journal of scientific Research and Engineering Development, 3(3), 735-746
[3]. Dishroon, D. (1983). Global Basin classification system. American Association of Petroleum Geologists Bulletin, 67(12). DOI: https://doi.org/10.1306/ad460936-16f7-11d7-864500012c865d
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[5]. Emery, D. and Myers, K. J. (1996). Sequence Stratigraphy. Blackwell Science Ltd., Oxford, 297 pp. DOI: https://doi.org/10.1002/97814443710

A dysregulated immune response to infection causes sepsis, a potentially fatal illness that, if left untreated, can cause organ failure and a high death rate. The danger of delayed discovery is increased in non-critical care wards because they rely on occasional manual observation, while intensive care units are the primary locations for continuous monitoring equipment. This paper proposes an embedded early sepsis detection system with the use of NanoEdge AI Studio for the training of an anomaly detection model on the STM32 microcontroller. Biomedical sensors are used to continually.........

[1]. K. E. Rudd et al., "Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the Global Burden of Disease Study," The Lancet, vol. 395, no. 10219, pp. 200–211, Jan. 2020.
[2]. F. Edathadathil et al., "Epidemiology of Community-Acquired Sepsis: Data from an E-Sepsis Registry of a Tertiary Care Center in South India," Pathogens, vol. 11, no. 11, Art. no. 1226, pp. 1–14, Oct. 2022.
[3]. PhysioNet, "PhysioNet/Computing in Cardiology Challenge 2019: Early Prediction of Sepsis," 2019. [Online]. Available: https://physionet.org/content/challenge-2019/1.0.0/
[4]. V. Abromavicius and A. Serackis, "Sepsis prediction model based on vital signs related features," Sensors, vol. 20, no. 15, Art. no. 4235, pp. 1–15, Aug. 2020.
[5]. I. Krissaane, K. Hampton, J. Alshenaifi, and R. Wilkinson, "Anomaly detection semi-supervised framework for sepsis treatment," IEEE Access, vol. 9, pp. 19364–19375, 2021.

IoT-based applications are becoming more popular and provide effective solutions for many real-time problems. In this project, real-time monitoring and a prepaid system for energy monitoring system are proposed. A solution is a cheap and easy-to-implement and manages energy monitoring system for our daily usage of electric power. In order to overcome human errors, manual labor and cost reducing in energy consumption with more efficiency for the power management system, in this project, we focus mainly on IoT prepaid energy monitoring..........

[1] Bharathy D, DhivyaC, Monisha A, Rathipriya S, Sikkandhar Batcha J- Smart Energy Meter Monitoring over IOT- International Journal for Modern Trends in Science and Technology (IJMTST)- Vol.06, Issue 06 -June 2020 - page no.[520-523]
[2] Manisha Tejwani, Prachi Rane, Moin Syed, Oyesh Patel, Pragyan Pandey - Iot Based Smart Energy Meter Monitoring and Billing System- International Journal of Innovative Technology and Exploring Engineering (IJITEE)- Vol.9 ,Issue 06 - April 2020 -page no.[1480-1483]
[3] NaziyaSulthana, Rashmi, Prakyathi N, Bhavana S - Smart Energy Meter and Monitoring System using IoT-International Journal of Engineering Research and Technology (IJERT)- Vol. 8, Issue 14, 2020- page no.[50-53]
[4] Nitesh D.Bhavsar, Mansi D.Mahajan, Omkar V.Joshi, D.Y. Thorat- IoT Based Prepaid Energy Meter-International journal of research and technology(IJRT)- Vol.4 ,Issue 3, 2019- page no.[16-18]
[5] Ranganayaki V, Nithish Kumar S , Subash, Mahaprabhu- IOT BASED PREPAID ENERGY METER- International Journal of Creative Research Thoughts (IJCRT)-Volume 9, Issue 7 July 2021-page no[219-224]

Examination malpractices remain a major challenge in both online and offline examination systems. Traditional methods such as human invigilators and CCTV surveillance require continuous monitoring and are prone to human error. This review paper presents an AI-Based Smart Exam Desk designed to enhance examination integrity using computer vision and intelligent monitoring. The proposed system integrates a Raspberry Pi, spy cameras, RF detection modules, and AI-based behavior analysis to automatically detect suspicious activities such as abnormal head movements.........

[1] J. Sharma, R. Verma, and P. Singh, "AI-Based Cheating Detection in Online Exams Using Computer Vision," in Proc. IEEE Int. Conf. on Intelligent Systems, pp. 210–215, 2022. [2] A. Patel, K. Mehta, and S. Desai, "Stress Detection Using GSR and Heart Rate Monitoring," Int. J. Eng. Res. Technol. (IJERT), vol. 10, no. 5, pp. 45–50, 2021. [3] S. Kumar and R. Gupta, "Smart Surveillance System Using IoT and Embedded Platforms," Int. J. Computer Applications, vol. 176, no. 18, pp. 12–17, 2020. [4] A. Rosebrock, "Practical Computer Vision with OpenCV and Python," PyImageSearch, 2019. [5] Raspberry Pi Foundation, "Raspberry Pi 4 Model B Datasheet," 2023. [Online]. Available: https://www.raspberrypi.com

Traditional farming methods face significant efficiency challenges due to unpredictable environmental factors, resource wastage, and manual monitoring constraints. Many studies show that improper irrigation and soil management lead to substantial crop yield losses, making precision farming necessary. Although automated irrigation systems exist, most operate on fixed schedules and lack intelligent decision-making based on real-time soil health. Similarly, while IoT systems are used for tracking climate data, they often lack integrated actuation mechanisms, and AI-based.........

[1]. Correa-Quiroz, J. J., Toribio-Barrueto, M. A., & Castro-Vargas, C. (2025). "IoT System with ESP32 for Smart Drip Irrigation and Climate Monitoring in Greenhouses." Emerging Science Journal, 9(3), 1133–1157. Why this matches: This paper specifically highlights the 35–40% reduction in water/waste, the use of the ESP32, and the integration of real-time cloud data (Arduino/Blynk) for intelligent decisionmaking. [2]. Impact of Environmental Factors & Yield Loss Reference: Sanjeetha, R., & Abeygunawardhana, P. K. W. (2024). "IoT Based Smart Agriculture System Using ESP32." ResearchGate. Detail: This study quantifies how improper water management reduces yields and argues for realtime monitoring to prevent the 40% loss mentioned in your text. [3]. IoT & ESP32 Microcontrollers Reference: Singh, P., et al. (2023). "Internet of Things Based Smart Irrigation System Using ESP WROOM 32." Journal of Internet of Things, 5(1). Detail: Focuses on the transition from fixed-schedule irrigation to real-time data-driven systems using the ESP32. [4]. AI and Machine Learning in Agriculture Reference: MDPI Agriculture Journal (2023). "Smart Irrigation Systems: A Comprehensive Review of IoT, AI, and Sustainable Agriculture Technologies