Agriculture plays vital role in the development of agricultural country like India. Issues concerning agriculture have been always hindering the development of the country. The only solution to this problem is smart agriculture by modernizing the current traditional methods of agriculture. Hence the proposed method aims at making agriculture smart using automation and IoT technologies. Internet of Things (IoT) enables various applications crop growth monitoring and selection, irrigation decision support, etc. A Raspberry Pi based automatic irrigation IOT system is proposed to modernization and improves productivity of the crop. main aim of this work to crop development at low quantity water consumption, In order to focus on water available to the plants at the required time, for that purpose most of the farmers waste lot time in the fields. An efficient management of water should be developed and the system circuit complexity to be reduced. The proposed system developed on the information sent from the sensors and estimate the quantity of water needed. A two sensors are used to get the data to the base station the humidity and the temperature of the soil, the humidity, the temperature, and the duration of sunshine per day. The proposed systems based on these values and calculate the water quantity for irrigation is required. The major advantage the system is implementing of Precision Agriculture (PA) with cloud computing, that will optimize the usage of water fertilizers while maximizing the yield of the crops and also will help in analyzing the weather conditions of the field.

IoT based smart crop-field monitoring and automation irrigation system

Fuzzy Logic based Smart Irrigation System using Internet of Things

Purpose- Agricultural production is under heavy pressure based upon increasing world population and significant changes in the climate. In this study, the concept of digital agriculture practices and their effects on agricultural productivity is discussed. An evaluation of current circumstance is made through the cases of Doktar Inc. and Tarla.io which are digital agriculture companies located in Turkey. Methodology- This study has utilized case method to evaluate the current circumstance of digital agriculture applications in Turkey. Since digital agriculture is an area that is still in early development stage in Turkey, case method is one of the most suitable methods. 11 open-ended questions and subsequent interviews sent to Doktor Inc and Tarla.io General Managers via e-mail and answers are evaluated with other collected data. Findings- Digital agriculture applications are in the early development stage in Turkey. The companies that are discussed in the paper have made meaningful progress regarding raising awareness of farmers and other involved parts of agriculture sector in Turkey. While the penetration of the two companies is currently not enough both as volume and quantity, the applications used for digital agriculture by them are parallel with the applications in developed countries. Conclusion- Digital agriculture practices in Turkey have yet to be implemented in very limited, but there are steps to be taken to acceleration. To develop digital farming in Turkey, supports of government have strategic priorities. In this context, the development of a digital agriculture action plan and supporting of this strategy with related policies and implementations, like in the EU countries and USA, will enable the expansion of agricultural production vision in Turkey. Technopolis and incubation centers of universities will be able to transform the accumulated scientific knowledge into initiatives and create a digital agriculture-focused ecosystem.

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Digital agriculture practices in the context of agriculture 4.0

The Internet of Things (IoT) is an element of worldwide data that comprise of web associated items, or things implanted with gadgets, software, sensors and also different instruments which are becoming an integral component of future internet This work developed a system which will automatically monitor the agricultural field as well as performing live video streaming for monitoring the Agriculture field from the server itself, through raspberry pi camera The agriculture fields are monitored for environmental temperature, humidity and soil moisture The automatic irrigation will be performed based on the set points of the temperature, humidity and soil moisture sensor The data collected from the field are monitored in IoT, the data are then processed and necessary information is passed through the field owners for counter measures

A sustainable agricultural system using IoT

Agriculture plays an important role in the making and development of a country. In India, agriculture is the primary source of living for more than about 60% of its population. The agriculture-related issues always hinder the development of a country. The enhancement of traditional agriculture methods and its modernization towards smart agriculture is the only solution for agriculture problems. Hence, by considering this issue, a framework is presented for smart agriculture using sensor network and IoT. The key features of this system are the deployment of smart sensors for the collection of data, cloud-based analysis, and decision based on monitoring for spraying and weeding. The smart farming approach provides valuable collection of data, high precision control, and automated monitoring approach. The proposed system presents smart agriculture monitoring system that collects and monitors the soil moisture, environmental temperature, and humidity. The measured soil moisture, temperature, and humidity are stored in ThingSpeak cloud for analysis.

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IoT-Based Framework for Smart Agriculture

Smart precision based agriculture makes use of wireless sensor networks to monitor the agricultural environment. Zigbee and raspberry pi-based agriculture monitoring system serves as a reliable and efficient method for monitoring agricultural parameters. Wireless monitoring of field not only allows user to reduce the human power, but it also allows user to see accurate changes in it. It focuses on developing devices and tools to manage, display and alert the users using the advantages of a wireless sensor network system. A smart system based on precision agriculture would pave the way to a new revolution in agriculture. The user can monitor the agriculture environment from a remote location, thus providing a greenhouse condition for the plants. India being an agro based economy; precision agriculture can bring about an improvement in the primitive methods, thus developing the country stature hugely. General Terms Sensor networks, smart agriculture.

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Smart Precision based Agriculture using Sensors

Due to the advanced multimedia editing tools and supported by sophisticated hardware, creating image/video manipulations for malicious purposes is increasing which is almost impossible to detect manually. Moreover, to conceal the traces, different post-processing operations are performed. Therefore, authenticity is a growing concern and important for identifying original and forged images. One of the popular image manipulations is copy-move forgery in which one or more regions in the image are duplicated to create a malicious effect within an image. The work in this article presents redundant wavelet transform based complex Zernike moment and Scale Invariant Feature Transform (SIFT) keypoint matching technique for copy-move image forgery operation detection. SIFT is robust against scale and rotation that works on identifying similarity using exhaustive search of SIFT features. After extracting SIFT keypoint features agglomerative hierarchical clustering is employed for grouping and key point matching operation is performed. Finally, block matching operation is evaluated and forged regions in the manipulated images are marked and displayed. This work also presents optimized SIFT key-point feature computations resulting in lower computation time, often one of the requirements in real time deployment. The proposed algorithm performance is evaluated using Precision, Recall, F-Measure and average detection accuracy on popular and publicly available MICC-220 database. The proposed technique demonstrates improved speedup and detection rate compared to existing approaches. Keywords—Forgery detection; scale invariant feature transform; key point operation; block matching; agglomerative hierarchical clustering

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K. Lakshmisudha

Papers

Smart Precision based Agriculture using Sensors

Optimized Image Authentication Algorithm using Redundant Wavelet Transform Based Sift Descriptors and Complex Zernike Moments