Showing papers in "International Journal of Advance Research, Ideas and Innovations in Technology in 2021"

IoT based home automation using FPGA

Abstract: A comfortable lifestyle is improving with the advance in technology day by day. Internet helps us provide any required information which any individual wants. IoT abbreviation for Internet of things helps us not only to get a comfortable lifestyle but also helps us to establish smooth and errorless transfer in communication. In-Home automation any appliance can be connected through IoT and can be used by our smart phones through application. Home automation is the future of smart homes. Wireless Communication using Wi-Fi is always placed into consideration compared to wired communication, as it is not only reliable but also easy to use. Wireless Communication like Bluetooth, Zigbee has a very short range. IoT uses WiFi to transfer data and it also helps to transfer data over a long-range using Static IP addresses and the Internet. FPGA helps to establish smooth connection between FPGA and home appliances. FPGA board provides high security and flexibility to the circuit. Home appliances are controlled using an FPGA board and it receives commands in serial communication from IoT Module through the application in the smartphone. It can also give us alerts through our application and also through the web IP address which can be protected by a password. It can also help us in long-distance communication with home appliances. There are many more advantages that can help us lead a comfortable lifestyle with IoT and FPGA board.

IoT based smart home security system

Abstract: The research paper based on home & industrial security ,the system are already installed in various industries but they have some drawback. We are all the student of final year computer technology we are try to overcome the problem that are facing the industry in any accident or harmful damage like gas leakage & fire.

Deep Learning for engineering applications

Abstract: In this paper, we formulate a new artificial intelligence based deep learning formulation to solve engineering applications in domains, heat transfer (2D,3D), strength of materials (2D,3D), design of machine elements, 3D component analysis, 3D assembly analysis, fluid dynamics (2D,3D), Kinematics/Vibrations/control (2D, 3D). Our deep learning based Distributed Artificial Neural Network (DANN) formulation showed six orders of magnitute speed up in computational time and needed an everyday use laptop, not necessiating high end super computer servers for engineering applications analysis. Further, the accuracy of the engineering solution showed 99.9% accuracy and comparable to the conventional existing engineering applications analysis results.

Determinants of underpricing of IPO – A case study of Indian stock market

Abstract: The study aims to investigate the reasons of Under-pricing of IPO by analyzing the impact of various factors like Issue Size, Stockholder Ownership Structure and Underwriter Reputation on the Under-pricing of IPOs. The target market chosen was all the IPOs issued In the Indian Stock Market from the Year 2010 to 2019 i.e., 219 Companies, which included 88 Underpriced IPOs and 131 Overpriced IPOs. Initially, exploratory research was undertaken to probe deeper into the topic. After conducting the exploring research, causal research was finalized as the most suitable method to go ahead with. We analyzed the data using tools like Correlation and Regression on various software i.e., Excel and SAS (Enterprise Guide). We concluded the Research by stating a Negligible Positive Relationship of Under-pricing of IPO with Issue Size and a Strong Positive Relationship with QIB and HNI Ownership and a negative Relationship with Retail Investors and Reputation of Underwriters.

Sustainable toilets by using lightweight precast concrete panels

Abstract: With increasing concern over the excessive exploitation of natural aggregates, synthetic lightweight aggregate produced from environmental waste is a viable new source of structural aggregate material. The uses of structural grade lightweight concrete reduce considerably the self-load of a structure and permit larger precast units to be handled. BS EN 12504-4. 2004. Testing concrete. Determination of ultrasonic pulse velocity. The mechanical properties of a structural grade lightweight aggregate made with fly ash and clay will be presented. Indicated that water absorption of the green aggregate is large but the crushing strength of the resulting concrete can be high. The 28-day cube compressive strength of the resulting lightweight aggregate concrete with a density of 1590 kg/m^3 and respective strength of 34 MPa. Experience of utilizing the green lightweight aggregate concrete in the prefabrication of concrete elements is also discussed.

Public key encryption with keyword search

Abstract: Today's entrepreneur world demands huge storage for the data and elementary sharing of the same. Cloud storage serves the requirement of providing security to the files uploaded by the organizations. Security prior to uploading the data is provided by encrypting the files and creating keywords to shield the organizational secrets from strangers. The other challenge faced by the organizations is the Insider keyword guessing attack, which results in the hackers being the employees themselves. To address this variant of threat, We propose a system that has a hierarchy developed between the employees such that the higher-level employees can monitor the activities of the lower-level workforce by constructing a semi-generic Public Key Tree. The PK-tree is constructed by the support provided by the Hierarchical Public Key Encryption with Keyword search [HPEKS] a variant of the public key encryption with keyword search [PEKS]. It furthermore enjoys transparency to the owner provided the admin-1 verifies the user login and Admin-2 will send the OTP (One time Password) such as the secret key to the user to their Registered mail Id which will be used to secure the data and records the activity. The efficiency of the system is analyzed by eradicating the insider attack threat.

Air pollution monitoring using IoT

Abstract: As the world becomes more industrial to support the basic necessities and luxuries of life, adverse effects have been noticed in the environment. One of these adverse effects is air pollution. Air pollution has risen to such a level in certain regions of the world that it has started to cause health-related issues to all of the living beings dwelling in that region. The purpose of this paper focuses on designing and implementation an air pollution monitoring system based on the Internet of Things (IoT) that would read the levels of pollutants in the air and other air quality factors, and thereby transmit these readings via wireless communication to a smart cloud platform where all these readings can be displayed in a distinguished manner. Such a system is a vital need so as to check the atmosphere one life in, and thereby take precautionary measures to protect oneself and the surrounding nature.

Neural Networks based solution for Door Automation

Abstract: Face Recognition is one of the most common biometric strategies which has gained popularity because of the accuracy and security. This paper presents the implementation of a Convolution Neural Network architecture for door automation. This model is devised to overcome the disadvantages of a traditional door system and other methods such as door automation using Bluetooth, figure prints, passwords, or retinal scans. It allows the authorized people to gain access to the house by face recognition. The proposed system makes use of convolution neural network architectures and RaspberryPi. The ResNet architecture [6] is used to implement face recognition and runs on RaspberryPi. The images of the residents of the house will be used to train the model. If the person is a resident of the house, the face will be recognized and the lock will open, else it will be recognized as a human and an alarm will ring and an email alert consisting of the image of the person in front of the door will be sent to the owner. It has numerous advantages as it is user-friendly especially for senior citizens, lesser maintenance, does not require the residents to carry the keys and reduces the threat of robbery.

Asthma prediction using Machine Learning

Abstract: Patient telemonitoring brings about a conglomeration of huge measures of data about quiet illness direction. Notwithstanding, the possible utilization of this data for the early expectation of asthma in grown-ups has not been methodically assessed. The point of this examination was to investigate the information for building AI calculations that anticipate asthma before they happen. The investigation dataset involved 278847 records presented by grown-up asthma patients. Prescient displaying included readiness of preparing informational indexes, prescient component choice, and assessment of coming about classifiers. AI classifiers are utilized to foster these prescient models; including Random Forest, Logistic Regression, Decision Tree, and Naive Bayes strategy. Of the multitude of classifiers carried out, strategic relapse classifier brought about the most elevated expectation precision. Our investigation showed that AI methods have huge potential in creating customized choice help for ongoing illness telemonitoring frameworks. Future examinations may profit with a far-reaching prescient system that consolidates information with different elements influencing the probability of creating asthma. Approaches carried out for cutting edge asthma expectations might be stretched out to early mediation of persistent ailments in patients

A study on the organic food industry: Consumer perception

Abstract: This research paper drills deep into the Organic food market. Highlighting the aspect that awareness about the benefits of organic food consumption is already high and after looking at the current incidences of harm to human life because of consumption of unhealthy food products, it is only expected to increase. The research problem is to study the consumer perception towards organic food products in Western Mumbai. The study was undertaken to study the motivations, barriers, awareness levels, and demographic characteristics of our study population w.r.t. organic food products.

Deep Learning for real applications

Abstract: In this paper, we provide a new artificial intelligence based deep learning formulation Distributed Artificial Neural Network (DANN) for real applications, AC placement in a room, design of new car doors from existing 15 given car doors, with six orders of magnitute speed up in computational time and need an everyday use laptop, not necessiating high end super computer servers for real application design and analysis. Further, the accuracy of the real application solution showed 99.9% accuracy and comparable to the conventional existing engineering applications software results.

An investigation into arson in secondary schools in Kenya: A case of Homa Bay County

Abstract: Fire, if controlled, is a very important object in the school community, it is used in many areas in school organization; kitchen e.g.cooking food for students, labs e.g. bunsen burner, and in instructions’ workshops e.g.Fire baths for forging, soldering and welding and burning of rubbish; generally controlled fire help in the learning of students while uncontrolled fire is very dangerous and has its effects. The study surveyed the effects of fire in schools that lead to solutions. Surveys of causes of school arsons will help the community, the school management, and the Ministry of Education get solutions to schools’ burning. The purpose of the study was to find out the causes of fire and remedies. The study sought to establish the following objective to make known the probable causes of fire and to open a way for the opportunity to study fires in related academic discipline. The study was conducted in four, randomly selected; public secondary schools in Homa Bay County, that were affected by the fire and four secondary schools that never had a fire problem. The study used a survey research design. The study population was principals, teachers, students, and watchmen in those secondary schools. The interview was given at random, selection for a principal, 23 teachers, 47 selected students, and 2 watchmen in each of the 8 secondary schools randomly selected in Homa Bay County. Questionnaires were given to the rest respondents. Survey research was used to analyze data. Findings and recommendations will assist Educational stakeholders in Kenya such as the Ministry of Education, the Kenya Institute of Curriculum Development, curriculum developers, and teachers. The study discovered ways of controlling fires, show the importance of fires, and the open way forward to study fire as one of the safety regulations especially in sciences and Engineering. The knowledge will differentiate and categorize the kind of status of school fires.

Breast Cancer Tumor Detection

Abstract: Women in India confront serious fatalities such as respiratory difficulties, but some also confront serious diseases in the form of breast cancer, which differs for each lady; This dangerous illness has been detected in more than half of middle-aged women. Breast cancer is found by looking for lumps in women's breasts that look like tumors. These anomalies' cells can be treated right away if they're found. However, benign tumors, which are fully non-cancerous, can form lumps with cells of the same size and no structural changes between them. Machine Learning(ML) techniques are frequently utilized to create tools for physicians and diagnosis of carcinoma, which can dramatically improve patient survival rates. The goal of this project is to create a machine learning system that can predict if a tumor is benign or malignant, as well as visualize the properties of both cancers will next be illustrated via graph plotting. Support Vector Classifier(SVC), Logistic Regression, Decision Tree Classifier, and KNN are the used Machine Learning(ML) Algorithms for Breast Cancer Tumor Detection. To compare and assess the accuracy and ROC plotting performance of Machine Learning Classifiers.

Food wastage reduction

Abstract: There is growing evidence that a significant share of global food is thrown away, with concomitant detrimental repercussions for sustainability. Reducing food waste is a key sustainability challenge for the foodservice industry. Despite the significance of this issue to the global foodservice industry, the link between innovation practices and food waste management has received limited attention in the academic literature. This paper uses innovation management and social constructionism to investigate the interrelationships of foodservice provisions and innovations in waste management. It is based on the evaluation of food waste solutions and innovations that combine strategic dimensions of waste management with practice-driven initiatives, including incremental (processes and technologies) and radical innovations. The paper presents a range of waste management initiatives, showing that their implementation in the foodservice sector varies depending on management’s beliefs, knowledge, goals, and actions. The concepts discussed here could help practitioners to become more aware of the factors that drive the adoption of food waste innovations. The prevalence of food waste has been a subject of interest and discussion in recent years and researches is being done to find effective ways to curb it. It has been identified as a primary issue in the sustainability of food production and consumption, in addition to the sustainability of food supply chains. Food waste can be divided into avoidable and unavoidable waste. Avoidable waste includes edible food and spoiled/damaged edible food, while unavoidable waste consists of inedible food like bones, fruit peels, and eggshells among others. Research shows that in Finland, 5% of purchased food is wasted in households, and an average person wasted about 20-30 kg of food in a year. The average total amount of food wasted in households yearly is about 120-160 million kilograms. Household wastage could be intentional or not. Many of the food wastage in households could be a result of forgetfulness or negligence for the food expiry date. In countries like Finland with the high cost of living, consumers are inclined to buy food nearing its expiry date due to the discount shop sellers attach periodically.

Re-design the Classroom for Online Learning

Abstract: It is now impossible to assess the effect of deferent teaching methods and performance in a dynamic technical environment. With the pace of technical dominance in the education market, the old teaching pattern is obsolescent every day. It is necessary to research how emerging technology support teaching and the education of students. The younger generation is always technical than, the older generation. Therefore, new instructional approaches must be sought, in particular on technology to attract this generation. Integrating technology into a traditional educational institution is not an easy task, as students and academics rely on traditional methods of learning and are unwilling to change with the new technology. They are also more convenient with the current methods. The influence of technology in the education sector is, nevertheless, inevitable. This paper discusses how technology affects online education and its future.

Dynamic request redirection for mining system services under Heterogeneous Distributed System

Abstract: Generating the common patterns in transactional the database Apriori mining algorithm deemed among the most significant. Apriori mining algorithm is an association concept mining masterstroke algorithm. Enhanced possibility of the many-core processors allows one to update the algorithms and the applications in order to achieve the computing power from many-core sources, which finds sets of a regular item are higher in terms of machine usage and power of CPU. The simultaneous frequency item sets mining algorithms to provide the direction to resolve the problem of the distribution of candidates between processors.

Earthquake Prediction using Machine Learning

Abstract: Earthquake forecasting is one of the most significant issues in Earth science because of its devastating consequences. Current earthquake forecasting scientific studies focus on three key points: when the disaster will occur, where it will occur and how big it will be. Scientists can predict where an earthquake will occur but it has been a major challenge to predict when it will occur and how powerful it will be. When the earthquake happens, we must fix this project. Specifically, you predict the time left before laboratory earthquakes occur from real-time seismic data that will have the potential to improve earthquake hazard assessments that could save lives and billions of dollars in infrastructure.

Performance evaluation of non-hierarchical routing protocols for healthcare applications

Abstract: All wireless sensor network (WSN) is a network of spatially distributed sensors that monitor physical or environmental characteristics. Wireless Body Area Network (WBAN) is a subset of WSN. WBAN is a new technology that is gaining popularity these days, WBAN devices are critical in the process of health monitoring and patient monitoring. Routing protocols will play a critical role in improving the effectiveness of communication between nodes and increasing the lifetime of a WBAN. The development and study of WBAN routing protocols has become a popular research area in recent years, particularly for medical monitoring applications. The energy-aware and high lifetime of the network are important parameters in the patient monitoring, For Health care application requires a unique routing protocol to transmit the data to their intended destination. The different non-hierarchical routing protocols like RPL, CTP presented in this context, The existing algorithms cannot fully satisfy the application requirements. In this paper energy efficient and reliable routing protocol is proposed for healthcare applications, our proposed routing protocol improves the network lifetime and reduce the energy consumption by using a weighted method, we evaluated the performance of proposed routing protocol in various routing parameter and comparing with RPL, CTP routing scheme. the Experimental results shows that proposed routing protocol performs better when compare to other two routing scheme. It is the best replacement with existing methods.

Solar Energy for Refrigeration and Air Conditioning

Abstract: In today’s world, the demand for comfort has been growing at an exponential rate. The utilization of air-conditioning and refrigeration systems has increased, which results in higher costs and consumption of energy. It is one of the main constituents of Global Warming. For example, Indian market of air conditioners was of worth $4.3 billion in 2017and will be of $11 billion by 2023 with a mean growth of 17% per annum.[2] Consequently, India produced roughly 2.5 billion tonnes CO2 within the year 2018. As a result a substitute for conventional method of air conditioning is being searched. Use of solar energy in air conditioning and refrigeration can be a substitute. It help in reduction of the consumption, the demand, and therefore costs of energy, without decreasing the desired comfort. These systems help in air conditioning and may even be used for refrigeration purposes. The can easily be used in commercial and residential apartments, colleges, hospitals, hotels etc. In this paper we will discuss the functioning of these systems and future scope of solar power in air conditioning and refrigeration.

Coping Strategies of students of High School and College for Anxiety During the Pandemic

Abstract: Covid-19 pandemic has affected people across the globe who have experienced lockdowns, restrictions, social distancing which has impacted their psychological and mental health. Coping strategies are a cognitive and behavioural effort made by individuals to deal with challenges presented by stressful situations. This study attempts to understand the coping strategies commonly adopted by students. This study examines three different coping strategies-problem solving, seeking social behaviour and avoidance adopted by high school and college students, during the pandemic. The study tries to understand the types of coping strategies adopted by students to deal with the stressful situation and how they use ‘coping with hope’ as a coping strategy. Further, the study aims to understand whether the coping strategies are more problem solving focussed or more avoidance focussed during the pandemic for the high school and college students. 98 students were selected based on random stratified sampling and snow ball sampling techniques from Delhi Public School, Gurgaon, India. The questionnaire used for the study was based on Coping Strategy Indicator developed by Dr. James H. Amir Khan along with a self-designed questionnaire to understand the nature of activities indulged in by the subjects and their attitude towards coping with hope. Pandemic has led to an increase in stress and a higher emotional oriented coping. Family and social support helped to reduce avoidance oriented coping. The findings of the study show that during the pandemic students adopted higher avoidance coping strategy than problem solving and seeking social support coping strategy.

Embedded system design for the forced circulation system

Abstract: In today’s world, most people are shifting towards renewable energy resources like solar which is globally accepted. The Forced Circulation Solar Water Heater System is not well-known but is one of the efficient types of water heater systems. In our country, such a system uses old techniques and is also costly. But we had upgraded it using an Embedded design which is much better in the economical and easy upgrade.

House rate prediction system using Machine Learning

Abstract: Everyone's desire is to purchase a home. When it comes to getting the best price, some people spend more than the property is actually worth. To tackle this challenge, we devised a method for predicting the price of a property using Machine Learning's Linear Regression model. We took into account all of the factors that one considers when purchasing a home, such as the neighborhood, the number of bedrooms, and the number of restrooms. It will undoubtedly assist the buyer in obtaining the best possible price.

comparative study of the prevalence of thyroid disorders

Abstract: Thyroid hormone disorders are the commonest endocrine disorder in India and also the commonest preventable cause of mental retardation. The male and female ratio of the disease ranges from 4:1 to 7:1 Untreated hypothyroidism during pregnancy can lead to delays in growth and intellectual development in the baby. The present study focused on the comparison of prevalence of thyroid disorders on various aspects like Comparison of prevalence of thyroid disorder on the basis of age, on the basis of gender and on the basis of religion. The clinic-based study was conducted in the clinic Ranchi, in this study 305 patients are taken as sample who visited in the clinic for treatment of thyroid disorder (Hypothyroidism, Hyperthyroidism) from year sept 2015 to dec 2017. Patients of all age are included in the study. Out of the 305 patients with thyroid disorder 298 patients found to have hypothyroidism (98%) and 7 patients with hyperthyroidism (2%). On the comparison of disorders found that hypothyroidism is more prevalent than hyperthyroidism. Thyroid disorder is more prevalent in female than male. There is a high prevalence of thyroid dysfunction in female in Ranchi and need for similar studies from different regions of the country covering larger population are well appreciated.

Study on heat transfer analysis of AC condenser by varying materials and refrigerants

Abstract: An AC condenser is a vitally important part of an air conditioning system that performs much of the cooling function. The condenser causes latent heat rejection by the refrigerant. The design of the condenser can vary from system to system. One of the most commonly used designs is the finned tube design. The material of the tubes and the fins, become the decisive factor in the rate of heat rejection and ultimately in the performance of the condenser. In this work, an air-cooled finned tube condenser is designed for a vapor compression cycle-based air conditioning system. The modeling is done using Solidworks and the fluid flow and heat transfer analysis are done in Ansys. To evaluate the effects of different materials on the performance of the condenser, copper is used as the tube material while, Aluminium alloys, 1060, 6060, and 7050 are used for fins. Two different types of refrigerants, namely, R32 and R134a have been used for analysis. Thermal analysis is done to determine the temperature distribution and heat flux for different sets of materials and different refrigerants. By comparing the results obtained with different combinations, the optimal combination can be determined.

Stock price prediction using sentiment analysis of business domains and company-related news data

Abstract: Stock price of a company is volatile in nature but when considering long term prediction of stock price, it is dependent on the company's business model and feasibility of the environment for the company to work. This data related to company and domains in which company works is available on the internet through news media but it is an arduous task for one to keep track of all this data and perform predictions on stock prices. Proposed model in this paper takes sentiment from this available data and provides prediction of stock price in the future with deliberation of the market environment.

Smart IoT based chicks brooding system

Abstract: Brooding is the most critical period in the life of a chicken. During brooding period, day old broiler chicks do not have the capability to warm themselves, and if not properly monitored chicks would die because of the change in weather. This would mean a big loss to the poultry farmer or owner. So to be able to address this issue, this study aimed to explore smart sensing during brooding period. This process could help monitor the temperature and humidity of the chicken coop easily during brooding period and notify the farmer immediately. The researcher developed a prototype using DHT22 sensor with Arduino Microcontroller and GSM Module. The prototype was tested and evaluated in terms of reliability. The Brooding is the most crucial period in the life of a broiler chicken. This period is when the systems are still in the development stage and the immune system is still delicate and cannot fight diseases. The feathers are not yet fully grown and the chicks are still learning to eat and drink. Since day old chicks do not still have the capabilities to keep their body warm. They are very in danger to the environmental conditions like temperature and humidity level. It leads to sickness and worst death of if they are exposed to colder temperature.

Design of Culvert using Suitable Software

Abstract: At the time when required, there is a water canal or the natural stream which intersects the road or the carriageway width, the big problem for us is to know how to keep this stream of water flows away from the road so that the roadway should not get affected by such situations. And the vehicles which pass near that stream in the flood situations, should also not get affected by this natural disaster. So, looking at this purpose, the Culverts are must be constructed across these intersections. A Culvert is nothing but a structure that is designed for passing the water which is overflowing through the streams. In this research work, we discussed aspects of culverts required at the different locations. And the designs are done both manually as well as by taking the help of the design software. The Standard codes of the design of Bridges and Roads are used in this research work for compiling the design of the culvert part. Different software’s are used for designing a culvert. From the results, for the design engineer, this research will offer to optimize saving of effort and also the time, by looking into effectiveness or accuracy.

Traffic sign recognition and classification using CNN

Abstract: We investigate the present status of traffic sign classification and recognition talking about what makes it a particular issue of visual item characterization. With noteworthy cutting-edge results, it is not difficult to fail to remember that the area stretches out past explained datasets and ignore the issues that should be looked at before we can begin preparing classifiers. We talk about such issues, give an outline of past work done, go over openly accessible datasets, and present another one. Following that, arrangement tests are directed utilizing a solitary CNN model, further than utilized beforehand and prepared with dropout and softmax. We apply it over different datasets from Germany and Belgium, their convergences and association, beating people, and other single CNN designs for traffic sign characterization.

Preliminary phytochemical screening and Invitro antioxidant activities of “Antidesma alexitera L.” leaf extract

Abstract: There is no plant in the world that is non-medicinal, or which cannot be used as medicine is used as medicine. Folk or traditional systems of medicines always played an imperative role in the global healthcare system. Antidesma alexiteria L (Thalimaram), belongs to the Phyllanthaceae family. Antidesma species has been used in many traditional medicines to treat diarrhea, skin complaints, hemorrhages, and abdominal disorders. The present study focuses on the preliminary Phytochemical screening and evaluation of the antioxidant potential of Antidesma alexiteria L. For qualitative analysis, standard tests were used to identify phytochemicals present in the extract and confirmed the presence of carbohydrates, coumarins, glycosides, saponins, phenols, and phytosterols. Leaf extracts were also subjected to total phenolic content(TPC), total tannin content (TTC), and total flavonoid content(TFC). In quantitative estimation, the TPC content of each extract was 24.13, 32.65 & 3.89 mg of GA/g extract, TFC was 230.38, 493.85 &217.15 mg of Ru/g extract and total tannin were 613, 503 &39.67 mg of CTN/g extract respectively. Antioxidant properties of the three extracts were evaluated using DPPH assay, Nitric oxide scavenging activity, and total antioxidant activity. Ascorbic acid was used as standard. In DPPH free radical scavenging assay IC50 value of alcoholic, hydroalcoholic, and aqueous root extracts were found to be 650.7,534.1 and 7704.18μg/mL respectively. For the Nitric Oxide Radical Scavenging assay IC50 value of alcoholic, hydroalcoholic, and aqueous root extracts was found to be 928.9, 354.6, and 380.24 μg/mL respectively. The total antioxidant activity of the plant extracts was calculated from the calibration curve of ascorbic acid, and the results showed 49.76, 44.97 and84.14 mg of AA/g activity for ethanolic, hydroethanolic, and aqueous extracts respectively

Artificial Intelligence in weed control and management

Abstract: Weed control and management play a vital role in the economic system. As the presence of weeds along with the crops have the power to decrease the yield, hamper the harvest and also lessen the quality of the crop which could lead to increment in the production cost and also decrease the market value of the crop in case weeds are not controlled. Weeds also hinder with the application of pesticides and interfere with irrigation. Automation in weed control is an emerging technology. Sturdy weed management technology will control the weeds despite the variables in the field. This paper mainly focuses on the mechanisms of weed control and management and their future scope.