Review of Sustainable Irrigation Technological Practices in Agriculture

The paper focuses on the increasing demand for water and its impact on irrigated agriculture, emphasizing the importance of effective water management. It reviews the use of soil moisture sensors, IoT, big data analytics, and machine learning in agriculture, particularly in the context of Indian agriculture. The study explores the potential of IoT technologies, such as sensors, drones, and machine learning algorithms, to optimize water usage, minimize waste, and enhance crop yields. The role of big data analytics in sustainable water irrigation management and decision support systems is highlighted. The integration of IoT and sensory systems in smart agriculture is discussed, addressing both the challenges and benefits of implementing sensory-based irrigation systems. Additionally, the paper describes an automated irrigation system developed to optimize water use for crops, utilizing a distributed wireless network of sensors and a web application. The system, powered by photovoltaic panels, demonstrated significant water savings of up to 90% compared to traditional irrigation methods in a sage crop field. The system's energy autonomy and cost-effectiveness suggest its potential utility in water-limited and geographically isolated areas

Review of intelligent sprinkler irrigation technologies for remote autonomous system

Changing of environmental conditions and shortage of water demands a system that can manage irrigation efficiently. Autonomous irrigation systems are developed to optimize water use for agricultural crops. In dry areas or in case of inadequate rainfall, irrigation becomes difficult. So, it needs to be automated for proper yield and handled remotely for farmer safety. The aim of this study is to review the needs of soil moisture sensors in irrigation, sensor technology and their applications in irrigation scheduling and, discussing prospects. The review further discusses the literature of sensors remotely communicating with self-propelled sprinkler irrigation systems, distributed wireless sensor networks, sensors and integrated data management schemes and autonomous sprinkler control options. On board and field-distributed sensors can collect data necessary for real-time irrigation management decisions and transmit the information directly or through wireless networks to the main control panel or base computer. Communication systems such as cell phones, satellite radios, and internet-based systems are also available allowing the operator to query the main control panel or base computer from any location at any time. Selection of the communication system for remote access depends on local and regional topography and cost. Traditional irrigation systems may provide unnecessary irrigation to one part of a field while leading to a lack of irrigation in other parts. New sensors or remotely sensing capabilities are required to collect real time data for crop growth status and other parameters pertaining to weather, crop and soil to support intelligent and efficient irrigation management systems for agricultural processes. Further development of wireless sensor applications in agriculture is also necessary for increasing efficiency, productivity and profitability of farming operations

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Combining Multi-Agent Systems and Wireless Sensor Networks for Monitoring Crop Irrigation

[EN]Monitoring mechanisms that ensure efficient crop growth are essential on many farms, especially in certain areas of the planet where water is scarce. Most farmers must assume the high cost of the required equipment in order to be able to streamline natural resources on their farms. Considering that many farmers cannot afford to install this equipment, it is necessary to look for more effective solutions that would be cheaper to implement. The objective of this study is to build virtual organizations of agents that can communicate between each other while monitoring crops. A low cost sensor architecture allows farmers to monitor and optimize the growth of their crops by streamlining the amount of resources the crops need at every moment. Since the hardware has limited processing and communication capabilities, our approach uses the PANGEA architecture to overcome this limitation. Specifically, we will design a system that is capable of collecting heterogeneous information from its environment, using sensors for temperature, solar radiation, humidity, pH, moisture and wind. A major outcome of our approach is that our solution is able to merge heterogeneous data from sensors and produce a response adapted to the context. In order to validate the proposed system, we present a case study in which farmers are provided with a tool that allows us to monitor the condition of crops on a TV screen using a low cost device.European Commision (EC). Funding H2020/MSCARISE. Project Code: 641794European Commision (EC). Funding FP7/SPE/SME. Project Code: 283638European Commision (EC). Funding FP7/SP1/ENV. Project Code: 28294

Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review

Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations. Farm animals are a critical part of the global food supply chain, and there is increasing consumer interest in organically fed and humanely raised livestock, and how it impacts our health and environmental footprint. Wild animals are threatened with extinction by human induced factors, and shrinking and compromised habitat. This review sets the goal to systematically survey the existing literature in smart computing and sensing technologies for domestic, farm and wild animal welfare. We use the notion of \emph{animal welfare} in broad terms, to review the technologies for assessing whether animals are healthy, free of pain and suffering, and also positively stimulated in their environment. Also the notion of \emph{smart computing and sensing} is used in broad terms, to refer to computing and sensing systems that are not isolated but interconnected with communication networks, and capable of remote data collection, processing, exchange and analysis. We review smart technologies for domestic animals, indoor and outdoor animal farming, as well as animals in the wild and zoos. The findings of this review are expected to motivate future research and contribute to data, information and communication management as well as policy for animal welfare

A Review of Wireless Sensor Technologies and Applications in Agriculture and Food Industry: State of the Art and Current Trends

The aim of the present paper is to review the technical and scientific state of the art of wireless sensor technologies and standards for wireless communications in the Agri-Food sector. These technologies are very promising in several fields such as environmental monitoring, precision agriculture, cold chain control or traceability. The paper focuses on WSN (Wireless Sensor Networks) and RFID (Radio Frequency Identification), presenting the different systems available, recent developments and examples of applications, including ZigBee based WSN and passive, semi-passive and active RFID. Future trends of wireless communications in agriculture and food industry are also discussed

Decision Support System Data for Farmer Decision Making

The capacity of farmers and agricultural scientists to be able to make in-season decisions is dependent on accurate climate, soil and plant data. This paper will provide a review of the types of environmental and crop data that can be collected by sensors which can used for decision support systems (DSS) or be further interrogated for real time data mining and analysis. This paper also presents a review of the data requirements for agricultural decision making by firstly reviewing decision support frameworks and agricultural DSSs, data acquisition, sensors for data acquisition and examples of data incorporation for agricultural DSSs

Survey of Impact of Technology on Effective Implementation of Precision Farming in India

The advancements in technology have made its impact on almost every field. India being an agricultural country, proper use of technology can greatly help in improving the standard of living of the farmers. With varying weather conditions, illiteracy of farmers and non-availability of timely assistance, the farmers of this country could not get the best out of their efforts. Precision farming focuses mainly on the aspects that can improve the efficiency based on the data collected from various sources viz. meteorology, sensors, GIS, GPS, etc. The information pertaining to farmland (e.g., soil moisture, soil pH, soil nitrogen) and agro-meteorology (e.g., temperature & humidity, solar radiation, wind speed, atmospheric CO2 concentration, rainfall, climate change and global warming) are used as input parameters to decide the varying requirements of the crop cultivation. Historical farm land data are used as a means to decide on the kind of actions to be taken under a specific scenario. This paper surveys the existing methods of precision farming and highlights the impact of technology in farming. An overview of different technologies used in precision farming around the world and their implications on the yield are discussed. The methods adopted towards managing different types of crops, the varying environmental conditions and the use of realtime data being collected through sensors are also analyzed. Also, the need for dynamic approaches to assist the farmers in taking context specific decisions has been highlighted