Ayaz, M., Ammad-Uddin, M., Sharif, Z., Mansour, A., & Aggoune, E. (2019). Internet-of-Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk. IEEE Access, 7, 129551-129583. Retrieved from http://ieeexplore.ieee.org.ezproxy.csu.edu.au/stamp/stamp.jsp?tp=&arnumber=8784034&isnumber=8600701
In this article Ayaz, Ammad-Uddin, Sharif, Mansour & Aggoune highlight the potential of a range of technologies that could be incorporated into an IoT based agricultural system. The authors analyse an array of wireless sensors and the expected challenges of integrating these technologies with traditional farming processes. Their research focuses on assessing wireless sensors, IoT tractors, harvesting robots, communication protocols, smartphones, cloud computing, UAV’s, food safety and food transportation and their potential application into current agricultural systems such as soil sampling, irrigation, fertiliser, crop disease, pest management, yield monitoring, forecasting and harvesting. The article is very useful to my research topic, as Ayaz et al. have concisely analysed the majority of the sensors I am considering to use in my solution. The main limitation of the article is that it does not present an agricultural solution but rather reviews technology that could be used in a solution thus the authors need to research the use of the technologies they analysed in a real-world system to test their limitations as a complete integrated architecture. This article will be useful in my research for supplementary information about wireless sensors.
Bauer, J., & Aschenbruck, N. (2018). Design and implementation of an agricultural monitoring system for smart farming. 2018 Iot Vertical And Topical Summit On Agriculture – Tuscany (IOT Tuscany), 1-6. Retrieved from http://ieeexplore.ieee.org.ezproxy.csu.edu.au/stamp/stamp.jsp?tp=&arnumber=8373022&isnumber=8373016
In this paper, Bauer & Aschenbruck present a complete system for monitoring agriculture utilising IoT and a wireless sensor network primarily focusing on onsite assessment of a specific crop parameter namely, leaf area index (LAI). The authors use a network of photosynthetically active radiation (PAR) sensors to measure the transmittance of solar irradiation through to estimate the amount of the LAI. Their research focusses on assessing the viability of the use of the PAR sensors to measure LAI. They also discuss real-world applications, including environmental challenges and wildlife-related challenges. This article is useful for my research for the implementation of the PAR sensors and the real-world implementation discussion. The main limitation of the article is that it only covers LAI and no other issues related to agriculture. Therefore, the authors specify the need for integration with other systems and further real-world deployment to expand their preliminary experimental results. This article will not form the foundation of my research; nevertheless, it is useful for the discussion of real-world challenges.
Boobalan, J., Jacintha, V., Nagarajan, J., Thangayogesh, K., & Tamilarasu, T. (2018). An IOT Based Agriculture Monitoring System. 2018 International Conference On Communication And Signal Processing (ICCSP), 594-598. Retrieved from http://ieeexplore.ieee.org.ezproxy.csu.edu.au/stamp/stamp.jsp?tp=&arnumber=8524490&isnumber=8523828
In this paper Boobalan, Jacintha, Nagarajan, Thangayogesh, & Tamilarasu use moisture sensors to analyse the soil moisture level to inform an automated system of which crops need irrigation. This system also senses humidity, temperature and the presence of obstacles in the area, aiming to reduce human involvement for complete automation. The research focuses on the programming of a simulated area of soil with auto irrigation and live video feed. This article is useful to my research topic as it uses soil moisture sensors which are an important part of my proposed solution and it also introduced me to Thing Speak which is software for data collection in the cloud with advanced data analysis using MATLAB. The main limitation of the research is that it is not implemented in a real-world environment and only uses one of each sensor which does not give the authors the opportunity for wider experimental research. The authors indicate the need for further, more extensive, research to be undertaken using a real-world environment. This article will not be used directly in my research but provided me with useful supplementary information on moisture sensors and a new IoT analytics program entitled Thing Speak.
Dagar, R., Som, S., & Khatri, S. (2018). Smart Farming – IoT in Agriculture. 2018 International Conference On Inventive Research In Computing Applications (ICIRCA), 1052-1056. Retrieved from http://ieeexplore.ieee.org.ezproxy.csu.edu.au/stamp/stamp.jsp?tp=&arnumber=8597264&isnumber=8596764
In this paper Dagar, Som & Khatri propose a model of IoT sensors that collect information and send it over a Wi-Fi network to a server to actuate programmed procedures. The IoT sensors used are air temperature, soil pH, soil moisture, humidity and a water volume. The authors implement their system in a poly house, a closed environment similar to a greenhouse, with the use of smartphones for a user interface. Their research focuses on assessing the viability of this IoT system to automate farming. The article is useful to my research topic, as Dagar et al. analyse may of the sensors that I will be proposing in my solution. The main limitation of the article is that it does not cover security issues or communication protocols, both major components of IoT systems. The authors discuss the need to implement the system on a larger scale and the absence of interoperability between different sensors and systems as an obstacle for their future research. This article will be included in my paper as the authors have surveyed current agriculture methods used by farmers, and the problems they face, concerning the sensors they use.
Grimblatt, V., Ferré, G., Rivet, F., Jego, C., & Vergara, N. (2019). Precision Agriculture for Small to Medium Size Farmers — An IoT Approach. 2019 IEEE International Symposium On Circuits And Systems (ISCAS), 1-5. Retrieved from http://ieeexplore.ieee.org.ezproxy.csu.edu.au/stamp/stamp.jsp?tp=&arnumber=8702563&isnumber=8702066
In this article Grimblatt, Ferré, Rivet, Jego & Vergara propose a system that will be able to measure important parameters for plant growth through a set of sensors. The authors establish, through research, the most important parameters for plant growth as; soil moisture, soil nutrients, soil pH, soil temperature, soil texture, environment temperature, weather and light. Their research focuses on setting up, displaying and analysing the data from only three sensors; soil moisture, soil temperature and ambient temperature. This article is useful in my research as Grimblatt et al. research the importance of several parameters vital in plant growth. The main limitation is the simplicity of their system, encompassing only three sensors and live readings via an LED display. No values are stored, graphically displayed or wirelessly obtained or used to actuate any responses; all of these elements need to be developed and further researched by the authors. This article is useful to my research mainly for the discussion of the important parameters for plant growth.
Mahalakshmi J., Kuppusamy K., Kaleeswari C., & Maheswari P. (2020) IoT Sensor-Based Smart Agricultural System. In: Subramanian B., Chen SS., Reddy K. (eds) Emerging Technologies for Agriculture and Environment. Lecture Notes on Multidisciplinary Industrial Engineering, 39-52. Springer, Singapore
In this article Mahalakshmi, Kuppusamy, Kaleeswari & Maheswari propose an IoT system for monitoring and tracking agricultural produce by implementing IoT-based smart sensors. The research proposes a cloud platform for storing and processing smart agriculture data from a wireless sensor network. Mahalakshmi et al. also extensively research, and test, encryption and security processes for wireless sensor data to be transmitted over the open transmission medium. The article is useful to my research topic as the authors have suggested and tested security and encryption protocols. The main limitation of the article is that the authors have not created a system that collects data from a range of sensors, while they discuss a theoretical system they do not develop and test a wider system with several sensors operating in unison as needed for real-world applications. Further research needs to be undertaken with a more complex system in a real-world environment. The article will greatly contribute to my research in the sections for security and encryption.
Mat, M., Mohd Kassim, A., & Yusoff, I. (2018). Smart Agriculture Using Internet of Things. 2018 IEEE Conference On Open Systems (ICOS), 54-59. Retrieved from http://ieeexplore.ieee.org.ezproxy.csu.edu.au/stamp/stamp.jsp?tp=&arnumber=8632817&isnumber=8632697
In this article Mat, Mohd Kassim & Yusoff research a system built for monitoring plants with the help of several sensors including; light, humidity, temperature and soil moisture to automate an irrigation system. The authors develop a theoretical architecture for smart farming and display data that could be captured by this system. This article is useful to my research as Mat et al. suggest and analyse numerous IoT models and sensors for use in an IoT farming architecture. The main limitation of this article is that it is purely theoretical, and no real-world experimentation is undertaken, for this reason, the authors have indicated a further need to trial their architecture in a real-world environment. This article is useful to my research primarily for the analysis of the sensors presented in their proposed architecture.
Patil, K., & Kale, N. (2016). A model for smart agriculture using IoT. 2016 International Conference On Global Trends In Signal Processing, Information Computing And Communication (ICGTSPICC), 543-545. Retrieved from http://ieeexplore.ieee.org.ezproxy.csu.edu.au/stamp/stamp.jsp?tp=&arnumber=7955360&isnumber=7955253
In this article Patil & Kale research wireless sensor technology and propose a Remote Monitoring System (RMS) to collect real-time data from an agriculture environment. The authors develop an experimental system that provides alerts through Short Messaging Service (SMS) on temperature, relative humidity, light intensity, barometric pressure and proximity along with an Android app that is capable of displaying live readings and actuating basic procedures such as sprinklers and fans. This article is useful in my research as Patil & Kale have suggested a complete architecture that could aid agriculture. The main limitation of the article is that the system is purely theoretical and has had no real-world testing. The authors also do not discuss network security or communication protocols, two very important considerations for IoT platforms. This article will not form the basis of my research; however, it will be useful for supplementary information on proposed architectures for my solution.
Sushanth, G., & Sujatha, S. (2018). IOT Based Smart Agriculture System. 2018 International Conference On Wireless Communications, Signal Processing And Networking (Wispnet), 1-4. Retrieved from http://ieeexplore.ieee.org.ezproxy.csu.edu.au/stamp/stamp.jsp?tp=&arnumber=8538702&isnumber=8538438
In this article, Sushanth & Sujatha develop an IoT based wireless sensor network for monitoring the environmental conditions in an agricultural setting to improve crop efficiency and yield. The authors develop a system which can send SMS notifications and android application notifications for monitoring of temperature, humidity, moisture and pest animal movement. The system also allows for data examination and irrigation actuation through the android application. The article is useful to my research as it proposes a complete theoretical architecture for an IoT agricultural system. The limitation of the article is that it is only theoretical, with no system being developed or tested in an experimental or real-world deployment. Further research and testing are needed for a developed prototype to provide more extensive research results. This article will form part of my research for the theoretical discussions and research on a complete agricultural solution.
Thorat, A., Kumari, S., & Valakunde, N. (2020). An IoT based smart solution for leaf disease detection. 2017 International Conference On Big Data, Iot And Data Science (BID), 193-198. Retrieved from http://ieeexplore.ieee.org.ezproxy.csu.edu.au/stamp/stamp.jsp?tp=&arnumber=8336597&isnumber=8336563
In this article Thorat, Kumari & Valakunde propose an IoT based agricultural architecture for the detection of leaf disease, remote video monitoring, humidity sensing, temperature sensing and moisture sensing. Their research focuses on the use of Image Processing using OpenCV to match images taken from the camera to images of known leaf disease. This article is useful to my research as it provides an excellent example of Image Processing to detect anomalies in crops, an important topic of research for a holistic IoT agricultural architecture. The main limitation of the article is the few diseases it can detect; therefore, the authors indicate creating a wider library of leaf disease images. This article will form part of my research as I will be discussing the use of cameras to detect diseases and anomalies in crops.
Venkatesan, R., & Tamilvanan, A. (2017). A sustainable agricultural system using IoT. 2017 International Conference On Communication And Signal Processing (ICCSP), 763-767. Retrieved from http://ieeexplore.ieee.org.ezproxy.csu.edu.au/stamp/stamp.jsp?tp=&arnumber=8286464&isnumber=8286342
In this article Venkatesan & Tamilvanan develop a system that monitors an agricultural field providing live video, environmental temperature, humidity and soil moisture. The data collected is then processed, and relevant information is passed to the farmers via SMS for relevant actions to be taken. The research focuses on testing the prototype of this system in a simulated environment to ascertain any issues that may arise with a real-world architecture. This article is useful to my research for the theoretical system the authors propose is similar to the solution I am considering researching. The main limitation of this article is that it is only theoretical and no real-world experimentation is undertaken, the authors need to trial their architecture in a real-world environment. This article is useful to my research primarily for the analysis of the sensors presented in their proposed architecture.
Yule, I., & Pullanagari, R. (2012). Optical Sensors to Assist Agricultural Crop and Pasture Management. Retrieved from https://www.researchgate.net/publication/278700271_Optical_Sensors_to_Assist_Agricultural_Crop_and_Pasture_Management
In this article Yule & Pullanagari research a range of optical sensors to analyse crop growing. The authors investigate two, three and 16 channel VIS/NIR sensors which as respectively capable of estimating biomass, crude protein and nutritive parameters, enabling farmers to measure and manage crops with higher precision. The authors analyse a range of statistics gathered from the use of these sensors. This article is useful to my research as it analyses the use of these sensors to see if they are a viable inclusion into my solution, the ability to measure nutritive parameters in-situ would be of great benefit to an IoT farming architecture. The limitation of the article is that the results the authors obtain are varied and at times inaccurate when compared to the more consistent results obtained by sending samples to the laboratory. Further research is therefore needed to calibrate the sensors and alleviate false positives and false negatives. This article will be included in my research as it contains excellent research on obtaining live results for testing the level of nutrients in the soil.