Relevant bibliographies by topics / Arduino Soil NPK sensor

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Arduino Soil NPK sensor'

Author: Grafiati
Published: 7 June 2025
Last updated: 16 July 2025

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Journal articles on the topic "Arduino Soil NPK sensor"

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Kumar, L. Lenin, M. Srivani, Md Tabassum Nishath, T. Akhil, Arugula Naveen, and K. Charith Kumar. "Monitoring of Soil Nutrients Using Soil NPK Sensor and Arduino." Ecology, Environment and Conservation 30, suppl (2024): 239–46. http://dx.doi.org/10.53550/eec.2024.v30i01s.049.

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Evan, Agil, Moechamaad Sarosa, Lis Diana, Rosa Andri, Mila Kusumawardani, and Dimas Firmanda. "IoT-Based Grapevine Watering System Design and Soil Condition Monitoring." BIO Web of Conferences 117 (2024): 01007. http://dx.doi.org/10.1051/bioconf/202411701007.

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Cultivating grapevines can be in the yard or together with other plants so that grapes are a plant product that needs to be developed. If you cultivate grapevines by knowing the evaluation of the environmental conditions of the soil, to the need for nutrients and water consistently. Grape plants can be predicted for their quality and yield, and can even identify their development from bud to fertilization. By using an Arduino Nano microcontroller as a control system equipped with sensors to measure and monitor soil environmental conditions. The sensors are NPK, soil moisture sensor, temperatur
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Abdillah, Adinda, Muhammad Nanak Zakaria, and Waluyo Waluyo. "Determination of Quantity Fertilizer for Sugarcane Based on Wireless Sensor Network." Jurnal Jartel Jurnal Jaringan Telekomunikasi 12, no. 4 (2022): 208–11. http://dx.doi.org/10.33795/jartel.v12i4.350.

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Fertilization plays a very large role in crop yields if done in the right way, effective and efficient fertilization will be achieved if the soil fertility conditions are known in advance. However, the problem is that farmer fertilization is still carried out by means of estimates based on land area without estimating the factor of soil needs.In this study the system uses a Wireless Sensor Network where there are 2 nodes installed on the land to monitor the measurement of soil moisture, soil pH, and nutrients using soil moisture sensors, soil pH sensors, and NPK sensors. From these sensors, it
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K, Spandana, and Pabboju Suresh. "IoT Enabled Smart Agriculture using Digital Dashboard." Indian Journal of Science and Technology 16, no. 1 (2023): 1–11. https://doi.org/10.17485/IJST/v16i1.1680.

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ABSTRACT <strong>Objectives:&nbsp;</strong>To develop an IoT-based smart device to retrieve soil and water parameters by collecting and storing sensor-based data and to make crop recommendations. The primary goal of this work is to create a link between farmers and their farms.&nbsp;<strong>Methods:</strong>&nbsp;This work produces a smart device to predict suitable crop based on several parameters using a technical approach that makes use of the Internet of Things, Machine learning algorithms, and Sensor Networks. The Gaussian Naive Bayes algorithm is used in the Prediction module to predict
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Arafat, Agil Soni, Ari Yuliati, and R. Yovi Manova M. "Design of a Soil Nutrient Measuring Device for NPK (Nitrogen, Phosphorus, Potassium) Case Study of Cayenne Pepper Based on Arduino Nano V3 ATmega328P." ITEJ (Information Technology Engineering Journals) 8, no. 2 (2023): 57–62. http://dx.doi.org/10.24235/itej.v8i2.120.

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Fertile soil electronic soil is essential for plant growth, and its quality significantly impacts crop yields. To help farmers measure the nutrient content of their soil more easily and accurately, innovative technology is required. In this case study, we present the design of a soil nutrient measuring device for Nitrogen, Phosphorus, and Potassium (NPK) that focuses on cayenne pepper. The device uses NPK sensors that can detect soil nutrients when inserted into the ground. The data collected by the sensors is sent to an ARDUINO Nano V3 ATMEGA328P, where it is processed and displayed as analog
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Chaudhari, Bhushan, Sachin Kamble, Madhuri Patil, et al. "Soil Fertility Detection and Crop Prediction using IoT and Machine Learning." International Journal of Membrane Science and Technology 10, no. 2 (2023): 2391–98. http://dx.doi.org/10.15379/ijmst.v10i2.2855.

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India has huge agriculture heritage. This is the major source of livelihood for most Indian families. Farmers are seen to use fertilizers in inappropriate proportion to enhance crop yield which results in infertile land. To overcome this issue, to check the fertility level of the soil, environment conditions and predicting suitable crop and fertilizers required is need of hour. Soil fertility depends on nutrients like Nitrogen (N), Phosphorous (P), and Potassium (K). It is also affected by environmental factors such as temperature, moisture, humidity, etc. The proposed system provides a cost-e
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Senapaty, Murali Krishna, Abhishek Ray, and Neelamadhab Padhy. "IoT-Enabled Soil Nutrient Analysis and Crop Recommendation Model for Precision Agriculture." Computers 12, no. 3 (2023): 61. http://dx.doi.org/10.3390/computers12030061.

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Healthy and sufficient crop and food production are very much essential for everyone as the population is increasing globally. The production of crops affects the economy of a country to a great extent. In agriculture, observing the soil, weather, and water availability and, based on these factors, selecting an appropriate crop, finding the availability of seeds, analysing crop demand in the market, and having knowledge of crop cultivation are important. At present, many advancements have been made in recent times, starting from crop selection to crop cutting. Mainly, the roles of the Internet
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Bachhav, Sujal S., Aman A. Deshmukh, Lochana G. Kotangale, Yogesh A. Shaniware, and Rahul K. Bhise. "Smart Agriculture: IOT-Driven Soil Nutrient Management System." Journal of Agriculture and Ecology Research International 25, no. 6 (2024): 169–75. https://doi.org/10.9734/jaeri/2024/v25i6650.

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Soil fertility plays a crucial role in determining soil quality, as it indicates how effectively the soil can support plant growth in agriculture. By utilizing soil sensors and Arduino technology, it is possible to assess the nutrient content of the soil quickly. Nitrogen, phosphorus, and potassium (NPK) are key nutrients required for healthy crop production, and their levels must be measured to determine the additional nutrients needed to enhance soil fertility. NPK sensors can be employed to detect soil nutrient levels, providing valuable data to assess whether the soil is nutrient-rich or d
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Mohammed, Muzakkiruddin Ahmed, and Singathi Sanjay. "IOT based soil NPK monitor via Asynchronous Web-Server using NodeMCU." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (2022): 525–30. http://dx.doi.org/10.22214/ijraset.2022.45320.

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Abstract: The process of transforming on agricultural production and farming is rising and expanding as a result of the increasing need for food. Utilizing IOT in agricultural and crop production will increase its dependability for farmers, which is a pressing necessity. Crop yield must be enhanced as a result of the population's fast growth. The soil content N (nitrogen), P (phosphorus), and K (potassium) such as are more crucial for producing crops that are more productive. We can assess the crops's rate of nutrient absorption based on the minerals found in the soil. Agricultural yield suffe
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C. Sudha, Et al. "An IoT based Tree Specific Soil Nutrient Management System Using Neural Network for Cashew Cultivation." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 10 (2023): 499–506. http://dx.doi.org/10.17762/ijritcc.v11i10.8514.

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Anacardium occidentale commonly known as Cashew was introduced into India by Portuguese in 16th century. Farmers of Cuddalore District, Tamil Nadu in India, are interested in Cashew Cultivation due to its export market values. To achieve better yield from cashew cultivation, farmers need to supply balanced nutrition to the soil and by following intercropping method. In literature, Recent Technologies like Artificial Intelligence and IOT are widely used to predict dosage of the fertilizer to be applied. By examining the numerous connected ascribe success locations of Cashew orchards, it was pos
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Dissertations / Theses on the topic "Arduino Soil NPK sensor"

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Cruz, João Alexandre Batista da. "DESENVOLVIMENTO DE UM SENSOR DE UMIDADE DO SOLO PARA DETERMINAÇÃO DA FRENTE DE MOLHAMENTO." UNIVERSIDADE ESTADUAL DE PONTA GROSSA, 2013. http://tede2.uepg.br/jspui/handle/prefix/164.

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Made available in DSpace on 2017-07-21T14:19:38Z (GMT). No. of bitstreams: 1 Joao Alexandre Cruz.pdf: 7505097 bytes, checksum: 227ae1f1c6b1c1dd753fb648adc79f93 (MD5) Previous issue date: 2013-09-05<br>The knowledge and control of soil properties in gricultural cultivation, obtained from sensors at automated system, extend the possibilities of increasing the results of a culture. This work aims to develop an electrical measure sensor at low cost to determinethe soil moisture, test and evaluate the correlation between the readings and gravimetric soil moisture, considered standard to calibr
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Diniz, Anibal Mantovani. "Sistema automatizado de aquisição, em tempo real, de umidade e temperatura do solo na irrigação." Universidade Estadual do Oeste do Paraná, 2017. http://tede.unioeste.br/handle/tede/2995.

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Submitted by Neusa Fagundes (neusa.fagundes@unioeste.br) on 2017-09-01T19:08:17Z No. of bitstreams: 1 AnibalM_Diniz2017.pdf: 2918535 bytes, checksum: ae39600214cf1d4dcb6e70a9e1eaa150 (MD5)<br>Made available in DSpace on 2017-09-01T19:08:17Z (GMT). No. of bitstreams: 1 AnibalM_Diniz2017.pdf: 2918535 bytes, checksum: ae39600214cf1d4dcb6e70a9e1eaa150 (MD5) Previous issue date: 2017-03-08<br>The modern agriculture is based on the application of techniques, methodologies and equipment that optimize their processes, thus increasing agricultural production, reducing costs and interfering less i
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Book chapters on the topic "Arduino Soil NPK sensor"

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Raikar, Rajkumar, Basavaraj Katageri, Rajashri Khanai, Dattaprasad Torse, and Praveen Mannikatti. "Soil Moisture Detection Using Arduino Sensor and ANN Prediction." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9610-0_10.

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Prince Sahaya Brighty, S. "Nutrients Detection and Adulteration Analysis of Vegetables and Fruits for Pregnant Women Using Machine Learning." In Predicting Pregnancy Complications Through Artificial Intelligence and Machine Learning. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-8974-1.ch007.

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The accurate detection and analysis of NPK values in fruits and vegetables play a significant role in ensuring their optimal growth and health. The authors propose a system for NPK value detection and analyse fruits and vegetables using NPK sensors and identifying the vegetable and fertilizer recommendation based on NPK values using random forest and SGD algorithms. The proposed system involves inserting NPK sensor into the vegetable, which measures the NPK value, and processing the data using an Arduino board. The NPK values are then read from the serial monitor using Python and used to identify the vegetable using the random forest algorithm. The system also recommends suitable fertilizers based on the NPK values using the SGD algorithm. The system's accuracy is enhanced by using a dataset of NPK values for various vegetables and fruits. The results are displayed in Stream lit, a web application framework. The proposed system enhanced accuracy in NPK value detection and analysis, improved vegetable identification and fertilizer recommendation, leading to improved crop yield and quality.
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B., Swapna, S. Manivannan, and M. Kamalahasan. "IoT-Based Design and Execution of Soil Nutrients Monitoring." In Advances in Social Networking and Online Communities. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-9640-1.ch010.

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A sensor centers on using detectors beneath the surface of the soil. The applications require the sending of sensors beneath the ground surface. Henceforth, the sensors turn out to be a piece of the detected condition and may convey more exact detecting. Sensors like NPK (nitrogen, phosphorus, and potassium), soil moisture, and humidity are underground and impart through soil. Most of the applications for sensors are shrewd farming, natural observing of the soil, etc. In this chapter, moisture substance, NPK level of the soil in land is estimated utilizing the sensors, which send it to the centralized server through internet of things for checking. The authors introduce propelled channel models to portray the underground remote channel to consider the qualities of the expansion of electromagnetic waves in the soil. From this detection of soil, one can increase crop production as per the wealth and nutrient levels of soil.
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Kohli, Ankur, Rohit Kohli, Bhupendra Singh, and Jasjit Singh. "Smart Plant Monitoring System Using IoT Technology." In Handbook of Research on the Internet of Things Applications in Robotics and Automation. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9574-8.ch016.

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Plants play a vital role in maintaining the ecological cycle, and thus, to maintain the plant's proper growth and health, adequate monitoring is required. Hence, the aim of the chapter is to create a smart plant monitoring system using automation and internet of things (IOT) technology. This topic highlights various features such as smart decision making based on soil moisture real-time data. For this purpose, sensors like soil moisture sensor, DHT11 sensor, level sensor, etc. are used. The soil moisture sensor measures the level of moisture (i.e., water content of different plants). The signal will be sent to Arduino board when the moisture level drops below the marginal value, which triggers the pumping of water into the plant by the pump. When the moisture level reaches absolute value, the pump is halted. The other condition for this process is level sensor. Level sensor senses the water level in the tank and sends the information of water level value to Arduino board and Arduino board to cloud. The whole data about the plant monitoring will be sent to the cloud server.
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Ambika, N., and Krishnan Rajamany. "Enhanced Smart Irrigation Using Sensors." In Utilizing AI and Smart Technology to Improve Sustainability in Entrepreneurship. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-1842-3.ch017.

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The working of the framework is completed by coordinating soil dampness sensor, passive infrared sensor (PIR), and water siphon along with the Arduino board. The job of the dirt dampness sensor is to detect the dampness of the dirt and give its yield to the client. The water siphon will flood the field only whatever point the dampness of soil goes beneath the ideal edge worth. The arrangement was tried for one month and information on interruption recognition was handily gathered through the PIR sensor and the working of the water siphon is effortlessly managed without subterranean insect issue. The suggestion tries to overcome crop spoilage and also aims at providing good yield. To make the system better, a weather forecast is considered. Based on these parameters, a statistical study is done to maintain the water content of the ground. using the study outcome, the design is proposed.
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Limbo, Anton, Nalina Suresh, Set-Sakeus Ndakolute, Valerianus Hashiyana, Titus Haiduwa, and Martin Mabeifam Ujakpa. "Smart Irrigation System for Crop Farmers in Namibia." In Transforming the Internet of Things for Next-Generation Smart Systems. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7541-3.ch008.

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Farmers in Namibia currently operate their irrigation systems manually, and this seems to increase labor and regular attention, especially for large farms. With technological advancements, the use of automated irrigation could allow farmers to manage irrigation based on a certain crops' water requirements. This chapter looks at the design and development of a smart irrigation system using IoT. The conceptual design of the system contains monitoring stations placed across the field, equipped with soil moisture sensors and water pumps to maintain the adequate moisture level in the soil for the particular crop being farmed. The design is implemented using an Arduino microcontroller connected to a soil moisture sensor, a relay to control the water pump, as well as a GSM module to send data to a remote server. The remote server is used to represent data on the level of moisture in the soil to the farmers, based on the readings from the monitoring station.
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Sindhuja, Gone, and Dr K.Charith Kumar. "A LOW-COST ARDUINO - BASED DATA LOGGING SYSTEM TO MONITOR ENVIRONMENTAL PARAMETERS." In Futuristic Trends in Agriculture Engineering & Food Sciences Volume 3 Book 10. Iterative International Publisher, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bcag10p3ch2.

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Different storage conditions like Modified Atmosphere Packaging and Controlled Atmosphere Packaging provides best environment for storage but the cost makes it unavailable for small and marginal farmers so as to record the environmental parameters, development of the sensor for measuring the fruit respiration one can get to know the various parameters such as Temperature, Humidity, and the Level of Carbon dioxide which could be useful in assessing the possible storage conditions. In the first objective, the module is developed with the assemblage of different sensors such as MQ135 and DHT22 and the values have been recorded with the help of a data logger. In the second objective the values are calibrated with the actual working sensor and are made to be in line with it. In the third objective the actual experiment is carried out to measure the various parameters such as temperature, humidity, carbon dioxide. The acquired values are used in the assessment of post-harvest condition and come to the necessary conclusions, the values of temperature and humidity are on par with the values that are acquired with the commercial sensors (Campbell) installed at the greenhouse of soil and water conservation engineering. But the carbon dioxide values have shown deviation.
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Eldho, Reshma P., Mushtaqulla Baig, Shivram B. Singh, Unnathi J, and Pradeep B. "Smart Solution for Efficient Agriculture Management and Intruder Detection and Mobile Application." In Advances in Transdisciplinary Engineering. IOS Press, 2022. http://dx.doi.org/10.3233/atde220740.

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Farming is the backbone of the economy and the most basic form of employment in our nation. For day-to-day survival, a huge portion of the world’s population is reliant on agriculture. The majority of agriculture cannot be productive solely through physical efforts and activities alone. It must be managed by creative technologies and smarter solutions. The physical pressure and stress on the agriculture community has increased due to weaker harvesting. To solve this crucial aspect of farming, we combine IoT and SMS alerts by combining a clever water distribution system with a smarter technique. This paper follows a smart approach that includes a smart water irrigation and agro system with outstanding management for continuous field information monitoring system. The smart farming system utilizes arduino, moisture sensor, PIR sensor, temperature sensors and so on to accurately monitor the surrounding conditions. Preprogramming to a particular value based on the crop requirement actually helps an automatic crop care reducing the man power. Moreover, moisture and humidity level can be specified to allow automatic watering and crop safety during different seasons. Using the technology, the system can monitor and regulate temperature, moisture, and soil dampness of a specific crop. Each of these actions will be controlled by a server connected through the cloud, with the task being carried out by integrating sensors and Arduino. Decisions must be taken based on the observed results.
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M. Hatture, Sanjeevakumar, Pallavi V. Yankati, Rashmi Saini, and Rashmi P. Karchi. "Organic Farming for Sustainable Agriculture Using Water and Soil Nutrients." In New Generation of Organic Fertilizers. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.100319.

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The agricultural community/farmers are struggling to obtain higher rate of yield due to lack of poor knowledge about the soil and water nutrients and suitability of the organic crop for the soil. Most of the farmers use excessive chemical fertilizers in-order to increase productivity of their yield, without aware of side effects. The excess usage of chemical fertilizers by the farmers will have impact on the quality, fertility, and salinity of the soil. To overcome these issues and to promote Digital Agriculture concept we propose an IoT enabled sensor system for monitoring soil nutrient [NPK] and pH of irrigation water to reduce the manual laboratory method of testing and get the results via mobile application and to promote organic farming in the agricultural field. Smart organic farming based mobile application will further process these nutrients value to predict and suggests the suitable crop to grow and the usage of appropriate amount of fertilizer to maintain the soil fertility there by achieving optimum usage of chemical fertilizer because continuous and wrong usage of these chemical fertilizer have a harmful effect not only on soil but also on crops, we consume leading to unhealthy human life. The proposed mobile application also helps in establishing the connection between farmers and Agricultural Produce Market Committee (APMC) in order to avoid fragmentation of profit shares and attain Pricing uncertainty and marketing of the yields by avoiding the middle man. APMC is a state government body which ensures safeguard to the farmers from exploitation by large retailers and suggest the kind of crop to be grown with organic farming. India is well known to produce organic fertilizer which is produced by the waste of slaughterhouses, plant and animal residues, biological products and other natural resources. Thus, the proposed work helps the farmers in adopting stress-free organic farming practice by self-testing their field soil parameters for generating quick soil analysis reports and also helps in connecting with APMC to know the suitable crop for their agriculture land based on the soil and water analysis (SWA) report, dispensing the required amount of organic fertilizer to the soil based on soil and water nutrients analysis using IoT enabled sensor, funding/insurance to the crops in case of occurrence of unpredictable natural disaster in future and direct marketing facility without middle man and maintain sustainable agriculture. In the present era, the industry is at 5.0 levels but agricultural production is still at 2.0 levels. In this chapter a methodology for sustainable agriculture and increase the organic yield of the organic farming using the mobile and IoT technological approaches is presented. A former can obtain the advice and other information for growing the organic crop, organic certification, pricing for the organic yield, selling and other activities by using mobile application in his/her local language. By the proposed work with the ease of mobile application the farmers can perform self-test of their field parameters for generating quick soil and water analysis report, predicts and suggest the suitable organic crop, obtaining the suitable pricing by the APMC and organic certification and agreement to meet the sustainable agriculture. Further the soil fertility of the organic farm can be monitored using IoT enabled sensors which are remotely connected with the mobile application. The experimentation is performed at different agriculture fields with organic farming at six geographical separated villages at Bagalkot district of Karnataka state, India. The different agricultural lands with variety of soil samples is tested to measure the soil parameter such as moisture, temperature, humidity and NPK nutrient values. The pH value of the irrigation water is also determined including borewell, pond, rain, river water etc. available in the reservoirs and promising sustainability in the organic yield is obtained.
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Agrawal, Anurag Vijay, Lakshmana Phanendra Magulur, S. Gayathri Priya, Amanpreet Kaur, Gurpreet Singh, and Sampath Boopathi. "Smart Precision Agriculture Using IoT and WSN." In Handbook of Research on Data Science and Cybersecurity Innovations in Industry 4.0 Technologies. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-8145-5.ch026.

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In precision agriculture (PA), the internet of things (IoT) and wireless sensor networks (WSN) can be utilised to more effectively monitor crop fields and make quick choices. The sensors can be installed in crop fields to gather pertinent data, but doing so uses up some of their limited energy. The use of IoT and WSN for smart precision agriculture necessitates energy-efficient operations, location-aware sensors, and secure localization techniques. In this chapter, agricultural problems are identified using IoT and WSN technologies to rectify them. Pests, a lack of water supply, and leaf diseases can be identified for best solutions through pest identification and classification, soil and water conservation, and leaf issues. The integration of Arduino and various sensors is used in the IoT and WSN to solve the issues automatically. Securing energy conservation can be achieved through IoT and sensor systems using efficient programmes.
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Conference papers on the topic "Arduino Soil NPK sensor"

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Kumar, Sourav, Gulab Singh, and DishantYadav. "Enhancement of Arduino-Based Capacitive Soil Moisture Sensor." In 2024 IEEE India Geoscience and Remote Sensing Symposium (InGARSS). IEEE, 2024. https://doi.org/10.1109/ingarss61818.2024.10983984.

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Patni, Jagdish Chandra, Vuppu Surya Prakash, Gajjala Sri Vardhan Reddy, et al. "Smart Plant Irrigation System with Arduino Uno and Soil Moisture Sensor." In 2025 2nd International Conference on Computational Intelligence, Communication Technology and Networking (CICTN). IEEE, 2025. https://doi.org/10.1109/cictn64563.2025.10932429.

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Madhumathi, R., T. Arumuganathan, and R. Shruthi. "Soil NPK and Moisture analysis using Wireless Sensor Networks." In 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT). IEEE, 2020. http://dx.doi.org/10.1109/icccnt49239.2020.9225547.

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Masrie, Marianah, Ahmad Zahid Mohd Rosli, Rosidah Sam, Zuriati Janin, and Mohd Khairi Nordin. "Integrated optical sensor for NPK Nutrient of Soil detection." In 2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA). IEEE, 2018. http://dx.doi.org/10.1109/icsima.2018.8688794.

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Fan, Wei, Kevin A. Kam, Haokai Zhao, Patricia J. Culligan, and Ioannis Kymissis. "An Optical Soil Sensor for NPK Nutrient Detection in Smart Cities." In 2022 18th International Conference on Intelligent Environments (IE). IEEE, 2022. http://dx.doi.org/10.1109/ie54923.2022.9826759.

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Kumar, Matti Satish, T. Ritesh Chandra, D. Pradeep Kumar, and M. Sabarimalai Manikandan. "Monitoring moisture of soil using low cost homemade Soil moisture sensor and Arduino UNO." In 2016 3rd International Conference on Advanced Computing and Communication Systems (ICACCS ). IEEE, 2016. http://dx.doi.org/10.1109/icaccs.2016.7586312.

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Singh, Pushkar, and Sanghamitra Saikia. "Arduino-based smart irrigation using water flow sensor, soil moisture sensor, temperature sensor and ESP8266 WiFi module." In 2016 IEEE Region 10 Humanitarian Technology Conference (R10-HTC). IEEE, 2016. http://dx.doi.org/10.1109/r10-htc.2016.7906792.

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Kandwal, Akhilesh, Amit Shakya, Ayushman Ramola, and Anurag Vidhyarthi. "Development and Analysis of Novel IoT Based Resistive Soil Moisture Sensor using Arduino UNO." In Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India. EAI, 2021. http://dx.doi.org/10.4108/eai.27-2-2020.2303177.

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Gnanavel, S., M. Sreekrishna, N. DuraiMurugan, M. Jaeyalakshmi, and S. Loksharan. "The Smart IoT based Automated Irrigation System using Arduino UNO and Soil Moisture Sensor." In 2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT). IEEE, 2022. http://dx.doi.org/10.1109/icssit53264.2022.9716368.

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Dhatri P V S, Divya, M. Pachiyannan, Jyothi Swaroopa Rani K, and G. Pravallika. "A Low-Cost Arduino based Automatic Irrigation System using Soil Moisture Sensor: Design and Analysis." In 2019 2nd International Conference on Signal Processing and Communication (ICSPC). IEEE, 2019. http://dx.doi.org/10.1109/icspc46172.2019.8976483.

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