Central Control Research Articles

Association between multiple sclerosis and urinary levels of toxic metals and organophosphates: A cross-sectional study in Israel

BackgroundMultiple sclerosis (MS) is a multifactorial disease of uncertain etiology damaging myelin sheaths around axons of the central nervous system. Myelin protects the axon from potentially harmful exogenous factors. The aetiological role of environmental exposure metals and organophosphates is unclear. ObjectiveIdentify whether urinary levels of metals and organophosphates differed in MS patients and controls. MethodsWe recruited MS patients from Ziv Medical Centre and healthy controls. MS patients were evaluated according to Expanded Disability Status Scale into mild and moderate-severe conditions. Each participant provided a urine sample and completed epidemiological questionnaires. The levels of six metal (Aluminum, Cadmium, Chromium, Lead, Mercury, Nickel) and one metalloid (Arsenic) and common organophosphates pesticide metabolites (6 dialkylphosphates, DAP) were measured in urine using inductively coupled plasma-mass spectrometry and gas-chromatography mass-spectrometry. We compared cases with controls in terms of urinary levels of these compounds using Mann-Whitney and Kruskall-Wallis tests. ResultsUrinary cadmium and mercury levels were higher in the 49 MS patients than the 37 controls (p < 0.01). Cadmium levels were higher in moderate-severe MS patients (n = 24) than mild MS patients (n = 25) (p = 0.003). ConclusionUrinary cadmium and mercury levels were higher among MS patients than controls. Cadmium levels correlated with disease severity. Further studies are needed to explore potential causal pathways between these compounds and MS pathogenesis.

Four years of National Clean Air Programme (NCAP) in Indian cities: Assessment of the impact on surface ozone during the period 2018–2022

There is a significant increase in ozone at the surface and troposphere due to growing population, industrialisation and urbanisation. The initiation of National Clean Air Programme (NCAP) in 2019 marked a turning point in addressing air pollution in Indian cities. The Central Pollution Control Board (CPCB) ground-based measurements show a reduction in number of days with continuous exposure to 8 h surface ozone (MDA-8) exceeding 100 ppb since the implementation of NCAP. For instance, cities such as Visakhapatnam and Tirupati reported zero days of MDA-8 ozone surpassing 100 ppb in 2022. Also, a substantial reduction is observed in the frequency of MDA-8 ozone exceeding the 100 ppb threshold at other stations. The NO2 and PM2.5 measurements from CPCB show a decreasing trend at most stations, whereas satellite-based HCHO and NO2 measurements show negative (0–0.004 mol m−2 month−1) and positive (0–0.02 m−2 month−1) trends, respectively, during the period of 2019–2022. Therefore, although the implementation of NCAP is oriented towards reducing PM10 concentrations, it is also proven to be effective in curbing ozone pollution in most cities of India. This study, therefore, suggests to continue the efforts of NCAP and to implement tailored regulations for reducing ozone pollution in cities with high pollution.

TPAAD: Two‐phase authentication system for denial of service attack detection and mitigation using machine learning in software‐defined network

AbstractSoftware‐defined networking (SDN) has received considerable attention and adoption owing to its inherent advantages, such as enhanced scalability, increased adaptability, and the ability to exercise centralized control. However, the control plane of the system is vulnerable to denial‐of‐service (DoS) attacks, which are a primary focus for attackers. These attacks have the potential to result in substantial delays and packet loss. In this study, we present a novel system called Two‐Phase Authentication for Attack Detection that aims to enhance the security of SDN by mitigating DoS attacks. The methodology utilized in our study involves the implementation of packet filtration and machine learning classification techniques, which are subsequently followed by the targeted restriction of malevolent network traffic. Instead of completely deactivating the host, the emphasis lies on preventing harmful communication. Support vector machine and K‐nearest neighbours algorithms were utilized for efficient detection on the CICDoS 2017 dataset. The deployed model was utilized within an environment designed for the identification of threats in SDN. Based on the observations of the banned queue, our system allows a host to reconnect when it is no longer contributing to malicious traffic. The experiments were run on a VMware Ubuntu, and an SDN environment was created using Mininet and the RYU controller. The results of the tests demonstrated enhanced performance in various aspects, including the reduction of false positives, the minimization of central processing unit utilization and control channel bandwidth consumption, the improvement of packet delivery ratio, and the decrease in the number of flow requests submitted to the controller. These results confirm that our Two‐Phase Authentication for Attack Detection architecture identifies and mitigates SDN DoS attacks with low overhead.

The control patterns of affective processing and cognitive reappraisal: insights from brain controllability analysis.

Perceiving and modulating emotions is vital for cognitive function and is often impaired in neuropsychiatric conditions. Current tools for evaluating emotional dysregulation suffer from subjectivity and lack of precision, especially when it comes to understanding emotion from a regulatory or control-based perspective. To address these limitations, this study leverages an advanced methodology known as functional brain controllability analysis. We simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data from 17 healthy subjects engaged in emotion processing and regulation tasks. We then employed a novel EEG/fMRI integration technique to reconstruct cortical activity in a high spatiotemporal resolution manner. Subsequently, we conducted functional brain controllability analysis to explore the neural network control patterns underlying different emotion conditions. Our findings demonstrated that the dorsolateral and ventrolateral prefrontal cortex exhibited increased controllability during the processing and regulation of negative emotions compared to processing of neutral emotion. Besides, the anterior cingulate cortex was notably more active in managing negative emotion than in either controlling neutral emotion or regulating negative emotion. Finally, the posterior parietal cortex emerged as a central network controller for the regulation of negative emotion. This study offers valuable insights into the cortical control mechanisms that support emotion perception and regulation.

Locational Suitability of Paschim Boragaon Landfill Adjacent to Deepor Beel Wetland, Assam

Deepor Beel, situated in the lower Assam region of Brahmaputra Valley, is a significant wetland that holds immense importance and is classified within the biogeographical region of the Burma monsoon forest. The beel acts as a crucial reservoir for storing water in Guwahati, aiding in mitigating the effects of flash flooding. The beel is endowed with luxuriant aquatic flora and fauna and maintains a well-balanced ecosystem. Nevertheless, the presence of the Paschim Boragaon Landfill in close proximity to the beel has raised concerns about the fragility of the biodiversity and ecosystem. The study was conducted to evaluate the appropriateness of placing a waste disposal site near a wetland and also how effectively did the Paschim Boragaon landfill adhere to the criteria specified in the Central Pollution Control Board (CPCB) and Central Public Health and Environment Engineering Organisation (CPHEEO). The landfill's establishment has disregarded the prescribed regulations imposed by the relevant governing body, posing a significant threat to the soil, water, and environment. This situation flagrantly violates the Wetland Rules of 2010, leading to detrimental effects on the diverse features and biodiversity of the beel. The landfill's close proximity has directly or indirectly disrupted the beel's heterogeneous characteristics. Hence, an urgent relocation of the entire landfill is imperative to protect the beel and uphold the internationally renowned Ramsar wetland's biodiversity.

Effects of central-peripheral FMS on urinary retention after spinal cord injury: a pilot randomized controlled trial protocol.

Urinary retention is a common complication of spinal cord injury (SCI), which can seriously affect the quality of life of patients. Function magnetic stimulation (FMS) has been widely used in the recovery of neurological function in various diseases, but its application in urinary retention after SCI remains unclear. Therefore, we would like to conduct a pilot randomized controlled trial (RCT) to observe the feasible effect of FMS on urinary retention after SCI, to explore its mechanism of action. This is a single-center pilot RCT, which 60 patients with urinary retention after SCI will be selected, numbered in chronological order of hospitalization, and randomly divided into 4 groups using the random number table method, Groups A (control group), Group B, Group C, and Group D; Each group will receive the same conventional rehabilitation treatment. The whole intervention period 2 weeks and will be evaluated before and after treatment to collect data on residual bladder volume, functional near-infrared spectroscopy (fNIRS), changes in voiding condition, changes in surface electromyography (SEMG) values of pelvic floor muscle and quality of life scores (QoL). We hypothesized that FMS for the treatment of urinary retention after SCI would have a significant clinical feasible effect;and that peripheral combined with central FMS would be more effective than single-site FMS for the treatment of urinary retention after SCI. (1) To illustrate the clinical effectiveness of FMS in the treatment of urinary retention after SCI and to provide a new treatment modality for the patients; (2) Comparison of the differences in the efficacy of central and peripheral single FMS and combined central and peripheral FMS in the treatment of urinary retention after SCI; (3) To explore the central control mechanisms of bladder function recovery after SCI in conjunction with changes in fNIRS. This study has been ethically approved by the Scientific and Ethics Committee of the First Affiliated Hospital of Gannan Medical university with approval number (LLSC-2022112401). It has been registered with the China Clinical Trials Registry with the registration number: ChiCTR2200067143.

Weather Forecast Control for Heating of Multi-Family Buildings in Comparison with Feedback and Feedforward Control

Our joint environmental and energy commitments mean we must reduce the building’s energy use. Improved central heating control can play a role in how this is accomplished. There are three common control strategies: feedforward (traditional), feedback, and model predictive control (MPC). The latter two often work in parallel, where feedback uses indoor temperature sensors to adjust the supply water temperature. In contrast, the supply temperature setpoint is continuously calculated in MPC, fed with weather forecasts. The weather forecasts are often highlighted as essential ingredients in MPC, but at the same time, it is emphasized that temperature sensors are used to ensure a pleasant indoor temperature. To an outside observer, it is difficult to determine what is what in such combined control arrangements. Is energy saved because of the room sensors or because of the model? And what role do the weather forecasts play? This study quantifies the impact of the control strategy on energy use and indoor temperature. It concludes that PI-based feedback heating control saves approximately as much energy as MPC, and weather forecasts do not save significantly more energy than real-time weather data but are easier to obtain. The overall results for both control strategies align with the lower end of the result ranges of previous studies. The novelty is that the impact of weather forecasts has been studied separately and that different control strategies are compared against each other based on a model of a typical Swedish multi-family building.

Longevity, demographic characteristics, and socio-economic status are linked to triiodothyronine levels in the general population.

The hypothalamic-pituitary-thyroid (HPT) axis is fundamental to human biology, exerting central control over energy expenditure and body temperature. However, the consequences of normal physiologic HPT-axis variation in populations without diagnosed thyroid disease are poorly understood. Using nationally representative data from the 2007 to 2012 National Health and Nutrition Examination Survey, we explore relationships with demographic characteristics, longevity, and socio-economic factors. We find much larger variation across age in free T3 than other HPT-axis hormones. T3 and T4 have opposite relationships to mortality: free T3 is inversely related and free T4 is positively related to the likelihood of death. Free T3 and household income are negatively related, particularly at lower incomes. Finally, free T3 among older adults is associated with labor both in terms of unemployment and hours worked. Physiologic TSH/T4 explain only 1.7% of T3 variation, and neither are appreciably correlated to socio-economic outcomes. Taken together, our data suggest an unappreciated complexity of the HPT-axis signaling cascade broadly such that TSH and T4 may not be accurate surrogates of free T3. Furthermore, we find that subclinical variation in the HPT-axis effector hormone T3 is an important and overlooked factor linking socio-economic forces, human biology, and aging.

Environmental Impacts of Emissions Streams Within the Ironmaking in Understanding SOX and NOX Formation Using Factsage Software

The manufacturing process of coke in steel plants, emits SOx and NOx which contributes around 30% of the total environmental pollution. The environmental norms from the Central Pollution Control Board of India may implement stringent norms on steel plants for their emission into its environment. In the present study, fact sage software was used for stimulating and quantifying the emissions like SOX and NOX in volume % by incorporating different possible operating parameters such as – its composition, suction pressure, flow rate, and fuel-to-air ratio. The simulation results were also compared with the plant data. The result showed peak flame temperature increased and also shifted toward a lower mixed gas-to-air-to-fuel ratio, indicating the combustion product at different mixed gas-to-air ratios. At an increased % of coke oven gas in mixed gas at a higher value of the mixed gas to air ratio, the percentage volume of COG was reduced. The new aspect of this work involves using a higher ratio of mixed gas to air, increasing the proportion of COG (carbonaceous gas) in the mixture, reducing the volume of CO2 produced, and increasing the formation of CO and SO2, indicating incomplete burning of hydrocarbons. However, when the COG decreases and the ratio of mixed gas to air increases, it leads to higher emissions of NOX. In the study the CEMS data matches with simulated results.

Agri-Water: An loT-based System for Sustainable Agriculture

Climatic conditions intricately influence agriculture, impacting optimal crop growth and reproduction through environmental factors. This study introduces a technological solution leveraging the Internet of Things (IoT), with Raspberry Pi 3 as the central controller. The system systematically collects crucial data on temperature, humidity, and soil moisture, ensuring the quality of crops. Subsequently, this information is used to formulate systematic crop watering plans. By efficiently using Raspberry Pi, the system regulates and monitors crops, contributing to water conservation by directing it precisely to the crops. This technology offers a practical and efficient approach to crop management, especially during challenging agricultural periods.

Frontal Crash Testing of a Class V Lift Truck

Abstract Counterbalanced, center control, high-lift trucks with a sit-down, non-elevating operator position are required to have a restraint system. The restraint system is intended to restrain the operator in the normal operating position and assist in reducing the risk of entrapment of the operator between the truck and the ground in the event of a tip-over. This is typically accomplished through the use of a two-point lap belt. This type of restraint also provides a degree of protection in the event of a collision between the lift truck and another object. Lift trucks operate in relatively low-speed environments, and many are limited to a maximum speed of 8 mph through a limiting device or by job site regulations. Though the speeds are low, lift trucks can operate in close proximity to other lift trucks and stationary rigid structures, creating the potential for collisions. The standards governing lift truck restraints do not mandate impact testing or injury criteria. This paper describes instrumented frontal impact and sled testing with a peak acceleration of 51 g performed on a Class V lift truck using an anthropomorphic test device (ATD) to test the effectiveness of lift truck restraints in this scenario. The results of this testing showed ATD injury metrics within automotive safety standards.

Synergy of W doping and oxygen vacancy engineering on d-band center modulation for enhanced gas sensing performance

W doping and vacancy engineering allowed the control of the d-band center of the material and improved the gas sensing performance.

The contribution of granger causality analysis to our understanding of cardiovascular homeostasis: from cardiovascular and respiratory interactions to central autonomic network control.

Homeostatic regulation plays a fundamental role in maintenance of multicellular life. At different scales and in different biological systems, this principle allows a better understanding of biological organization. Consequently, a growing interest in studying cause-effect relations between physiological systems has emerged, such as in the fields of cardiovascular and cardiorespiratory regulations. For this, mathematical approaches such as Granger causality (GC) were applied to the field of cardiovascular physiology in the last 20years, overcoming the limitations of previous approaches and offering new perspectives in understanding cardiac, vascular and respiratory homeostatic interactions. In clinical practice, continuous recording of clinical data of hospitalized patients or by telemetry has opened new applicability for these approaches with potential early diagnostic and prognostic information. In this review, we describe a theoretical background of approaches based on linear GC in time and frequency domains applied to detect couplings between time series of RR intervals, blood pressure and respiration. Interestingly, these tools help in understanding the contribution of homeostatic negative feedback and the anticipatory feedforward mechanisms in homeostatic cardiovascular and cardiorespiratory controls. We also describe experimental and clinical results based on these mathematical tools, consolidating previous experimental and clinical evidence on the coupling in cardiovascular and cardiorespiratory studies. Finally, we propose perspectives allowing to complete the understanding of these interactions between cardiovascular and cardiorespiratory systems, as well as the interplay between brain and cardiac, and vascular and respiratory systems, offering a high integrative view of cardiovascular and cardiorespiratory homeostatic regulation.

REGULATORY LANDSCAPE OF UNANI PRODUCTS UNDER D&amp;C ACT AND RULES

The Unani System of Medicine (USM), deeply rooted in tradition, undergoes scrutiny in India under the Drugs and Cosmetics Act (D&amp;C Act) for consumer safety. Regulated by the Central Drugs Standard Control Organization (CDSCO) and guided by the Ayurvedic, Siddha, and Unani (ASU) Drugs Technical Advisory Board, this framework ensures Unani product safety, efficacy, and quality. Manufacturers must comply with Good Manufacturing Practices (GMP), and the D&amp;C Act establishes standards for labeling, packaging, and quality control—essential for marketing Unani products in India. The paper aims to analyze key D&amp;C Act provisions related to Unani formulations, focusing on regulatory procedures. The study sheds light on specific requirements governing Unani drug import, manufacture, distribution, and sale, offering valuable insights into the regulatory framework. It systematically examines the D&amp;C Act, emphasizing sections related to Unani products. Unani Drugs must adhere to prescriptions in the 14 recognized Unani texts (Schedule I of D&amp;C Act). The Drugs and Cosmetics Rules of 1945 cover Unani Medicine in Parts 16 to 19, addressing licensing (Part 16), testing (Part 16A), labeling and packaging (Part 17), and quality control standards (Part 19). In conclusion, this paper provides a nuanced analysis of the regulatory landscape governing Unani products under the Drugs and Cosmetics Act. It elucidates legal intricacies, emphasizing challenges in compliance, standardization, and merging traditional knowledge with contemporary requisites. The insights contribute to understanding the regulatory environment surrounding Unani medicines, balancing cultural heritage preservation with ensuring efficacy and safety for consumers.

Time Series Analysis and Forecasting of Water Quality Parameters along Yamuna River in Delhi

The extent of pollution in areas near industrial activities and Yamuna River has increased tremendously and to determine the overall water quality status in these locations is utmost important. This paper presents a comprehensive study on assessing the water quality and gain insights into the overall water quality status in the vicinity of industries and along the Yamuna River in Delhi. To achieve this, water samples were collected from Central Pollution Control Board (CPCB) for the last eight years (2013-2021) and was converted into a machine-readable format to facilitate further analysis. These samples were analysed for several water quality parameters, including pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), nutrient levels, heavy metals, and other relevant pollutants. By understanding these factors, a deeper understanding of the pollution sources and their impact on water quality is gained. Time series methods are applied to forecast future trends and values of the water quality parameters. This allows for predicting potential changes in water quality over time. A remarkable accuracy of 93.6% is attained in predicting water quality values up to the present time. The analysis reveals that water quality in the NCR region falls below acceptable standards. However, there has been a marginal enhancement in the water quality at Khajori Paltoon (Location L3) post-COVID. To achieve a more significant improvement in water quality, it is imperative to implement new policies.

Hospital wastewater treatment using electrocoagulation: Performance, kinetics, settlement analysis, and cost-effectiveness

The hospital units conduct a wide range of activities and generate a massive amount of effluent, which contains a large variety of contaminated pharmaceuticals, radioactive elements, and chemicals. The increased chemical oxygen demand (COD), biochemical oxygen demand (BOD), turbidity, total hardness (TDS), nitrate, phosphates, and ammonium ions in wastewater have an unfavorable impact on all living forms of the ecosystem. Electrocoagulation (EC) is an adaptable technique for removing pollutants from wastewater, it has been used in this study to determine the optimal conditions utilizing several process variables, including pH, current density, time, and electrolyte dose. Up to 94%, 31%, 96%, 54%, 50%, and 22% respectively, less COD, BOD, turbidity, phosphate, nitrate, and ammonium ions were detected. Fecal indicator bacteria were significantly reduced. Subsequently, the treated water was evaluated for suitability of reuse in farming by comparing its parameters to those of the World Health Organization (WHO), the Central Pollution Control Board (CPCB), and Moroccan standards. After germination tests on radish beans, it was discovered that the EC-treated water was suitable for irrigation. The suitability of the implemented process was assessed by comparing it to advanced oxidation and biological approaches.

Impact of Lockdown on Air Quality in the Most Polluted Cities of India.

COVID-19 has become a global pandemic, prompting lockdowns in practically every country. To prevent the spread of the disease, India has enforced a rigorous nationwide lockdown that commenced in March 2020. The lockdown imposed amid the pandemic ensured that most commercial activities and vehicle transportation ceased, resulting in a significant reduction in air pollution levels. The value of air pollutants PM10, PM2.5, NO2, and SO2 from January to May 2020 was obtained from the Indian Central Pollution Control Board. Before lockdown and during lockdown, relative fluctuations in ambient concentrations of four air contaminants were investigated. The Box-Jenkins approach was used to estimate future air pollution data points using time series data analysis. The PM10 level reduced by 61%, 30%, 68%, 37%, and 43% in the selected cities, respectively. Comparison of other pollutant concentrations before and after the lockdown also found a reduction in ambient pollutant concentrations, resulting in improved air quality. Inference of predicted model values to observed values revealed a significant increase in the concentrations of all pollutants. The percentage increases in AQImean from predicted to observed values were 206% in Ghaziabad, 148% in Delhi, 59% in Hyderabad, and 160% in Cochin. The strict lockdown has resulted in a significant drop in air pollutant levels. Upgrading present technologies could help keep pollution to a minimum of 37% under control. The findings would prompt the government to consider how to strictly reduce vehicle and industrial pollution to improve air quality and maintain improved public health.

Exploring the use of bimodal transcranial direct current stimulation to enhance movement in individuals with patellofemoral pain-A sham-controlled double blinded pilot study.

In individuals with patellofemoral pain (PFP), addressing increased knee valgus during weight-bearing activities typically involves strengthening weak hip muscles. However, recent literature highlights the role of altered descending central control in abnormal movements associated with PFP. While transcranial direct current stimulation (tDCS) has demonstrated the capacity to enhance neuroplasticity, its application targeting the corticomotor function of gluteal muscles in PFP remains unexplored. This study aimed to investigate the effects of combining bimodal tDCS with exercise on frontal plane kinematics in individuals with PFP. The hypothesis was that bimodal tDCS, specifically targeting the corticomotor function of the gluteal muscles, would augment the effectiveness of exercise interventions in improving frontal plane kinematics compared to sham stimulation. Ten participants with PFP participated in two sessions involving either bimodal tDCS or sham stimulation, concurrently with hip strengthening exercises. Weight-bearing tasks, including single leg squat, single leg landing, single leg hopping, forward step-down, and lateral step-down, were performed and recorded before and after each session. Pain visual analog scale (VAS) scores were also documented. A one-way ANOVA with repeated measures was employed to compare kinematics, while a Friedman test was used to compare VAS across the three conditions (pre-test, post-tDCS, and post-Sham). We observed no significant differences in trunk lean angle, hip and knee frontal plane projection angles, or dynamic valgus index among the three conditions during the five weight-bearing tasks. VAS scores did not differ across the three conditions. A single session of tDCS did not demonstrate immediate efficacy in enhancing frontal plane kinematics or relieving pain in individuals with PFP. Considering observed positive outcomes in other neurological and orthopedic populations with multi-session tDCS applications, suggesting potential cumulative effects, further research is essential to explore the effects of multi-session tDCS on weight-bearing movement and underlying neurophysiology in individuals with PFP.

The Role of Central Oxytocin in Autonomic Regulation.

Oxytocin (OXT), a neuropeptide originating from the hypothalamus and traditionally associated with peripheral functions in parturition and lactation, has emerged as a pivotal player in the central regulation of the autonomic nervous system (ANS). This comprehensive ANS, comprising sympathetic, parasympathetic, and enteric components, intricately combines sympathetic and parasympathetic influences to provide unified control. The central oversight of sympathetic and parasympathetic outputs involves a network of interconnected regions spanning the neuroaxis, playing a pivotal role in the real-time regulation of visceral function, homeostasis, and adaptation to challenges. This review unveils the significant involvement of the central OXT system in modulating autonomic functions, shedding light on diverse subpopulations of OXT neurons within the paraventricular nucleus of the hypothalamus and their intricate projections. The narrative progresses from the basics of central ANS regulation to a detailed discussion of the central controls of sympathetic and parasympathetic outflows. The subsequent segment focuses specifically on the central OXT system, providing a foundation for exploring the central role of OXT in ANS regulation. This review synthesizes current knowledge, paving the way for future research endeavors to unravel the full scope of autonomic control and understand multifaceted impact of OXT on physiological outcomes.

Machine Learning based Precision Agriculture Model for Farm Irrigation to Optimize Water Usage

The food demand is ever increasing each year and to meet this demand precision agricultural approach using machine learning tools play an important role. Precision irrigation systems integrate cutting-edge technologies, such as sensors, controllers, data analytics and internet, to achieve sustainability in agriculture and maximize water use so as to improve crop production while minimizing water wastage and climate impact. The main purpose of this article is to find out the precise water requirements for a particular area of the land by using soil moisture sensors. These sensors provide real-time data that is transmitted to a central control unit, which utilizes data driven algorithms to analyze moisture levels in the soil and controls the water supply. Furthermore, the model developed offers remote monitoring and control capabilities, enabling farmers to access and manage the system from anywhere using mobile or web application. This feature allows farmers to remotely adjust irrigation schedules, receive real-time alerts and notifications, and track water consumption, promoting convenient and efficient management of water resources. Thus by using effective water management techniques such as precision irrigation, controlling the water quality, will accomplish optimizing water usage and intern optimizes the yield.