Internet of Thing (IOT) Based Sensor Technologies and Smart Irrigation System: An Analysis of Critical Success Factors in Emerging Markets

Agriculture is a separate economic sector. In agriculture, India ranks second. Agriculturists stress the need of fertilization and crop rotation. Today's farmers are unable to produce the maximum amount of food due to technological advancements. The major focus should be on using and collaborating with emerging technology in agriculture to boost output. The Internet of Things (IoT) helps estimate crop yields and other factors that contribute to high productivity. Soil temperature, pH, and water level all play a role in delivering optimal crops and increasing productivity. This study proposes "ACRIS: Agriculture Cultivation Recommender and Smart Irrigation System" to help farmers who use IoT in precision agriculture to increase crop output. The ACRIS system has three modules. "Accurate Farming Recommendations Using an Agriculture Factor-based Relevance Vector Analysis Model" is the first ACRIS module. Because of this, our model offers a more favorable situation based on relevant vector analysis. The second module is "AISM System: Advanced Irrigation Planner for Precision Farmers." The module forecasts soil moisture and organizes irrigation for farmers using precision agriculture to decrease water usage and boost productivity. The "AMOP System: ACRIS Multiparameter Optimization Systems for Precision Agriculture" module compares water content at different phases of plant development and integrates IoT technologies into agriculture to ensure optimal crop growth and water stability. The agricultural production is enormous, and it is vital to farmers' income.

Remote assistance needs to be automated for better coverage in time, quality, and quantity of clients. The problem is that by increasing the number of clients with the same amount of attention personnel or none, the waiting time of clients increases, and the quality of attention decreases. The objective of this research is to perform an analysis of the general critical success factors by simulating fuzzy cognitive maps applied to a chatbot for technical support. The methodology applied is exploratory, qualitative, descriptive research and de-duction to analyze the references on chatbots, technical support, critical success factors and fuzzy cognitive maps. This research resulted in a Definition of general critical success factors for a technical support chatbot, a Simulation of critical factors in a fuzzy cognitive map, an Analysis of critical success factors, and a general architecture prototype for the technical support chatbot. It was concluded that among the main critical factors for a project are important elements the knowledge of experts, expertise, and human resources; the application and analysis of CSF through FCM helps in the improvement and optimization of the factors/tasks of the chatbot project for technical support.

Developing countries such as India regards agriculture as the backbone. It plays a vital role in the growth of the Nation's economy. Despite the fact that the world is moving into new technology, agriculture must also be allowed to drift away. One such innovation is the Internet of Things (IoT). The Internet of Things (IoT) is defined as interconnecting different devices like sensors via the Internet. This paper proposes and tests a cloud-based wireless communication framework for tracking and managing a series of sensors and actuators for determining plant water needs and environmental parameters that impact plants. An ESP8266 Wi-Fi module-based automatic irrigation system and environment monitoring systems are implemented in this project. A smart irrigation system is implemented using soil moisture sensor which senses the moisture present in soil and actuates motor accordingly. For healthy growth of plants, it needs fresh and clean air; hence, it is monitored by MQ135 sensor called air quality sensor. The DHT11 sensor also known as temperature and humidity sensor is used for low-cost and more efficient monitoring of temperature and humidity. Blynk application in mobile is used to analyze all wireless sensor data through the cloud. These implementations will maximize the yield of the crops.KeywordsIoTSoil moistureAir qualityCloud computingWireless sensors

Water management in agriculture has been transformed by smart irrigation systems that use the Internet of Things (IoT) to maximize resource use and boost crop yields. IoT-based irrigation, which reduces waste and improves sustainability in the face of growing water scarcity, combines sensors, actuators and real-time data analytics to deliver accurate water flow. The use of IoT in agriculture is reviewed in this paper, which also covers AI-driven decision-making algorithms and communication technologies like LoRa, Zigbee and Wi-Fi. In agriculture, IoT has been widely employed in agriculture to enable better farming and redefine conventional practices. Some of the necessary applications include monitoring crops, monitoring livestock, automation of the supply of water through real-time data, promotion of optimal water consumption and wastage minimization. Furthermore, increased agricultural yields, cost savings and water conservation are just a few benefits of using IoT in irrigation systems. Research also claimed that when compared to traditional methods, IoT-based irrigation systems can save up to 30% on water usage. IoT-based irrigation has drawbacks despite its benefits, including costly upfront costs, complicated technology and cyber security threats. The use of self-powered sensors, AI-powered predictive irrigation and blockchain-enhanced data security are some of the upcoming trends. Smart irrigation systems have the ability to transform precision agriculture and guarantee both environmental preservation and food security by removing implementation obstacles. Future research should focus on enhancing interoperability among IoT devices, improving decision-making algorithms and developing cost-effective solutions for small-scale farmers. With continuous innovation and widespread adoption, IoT-driven smart irrigation has the potential to address global food security concerns while preserving water resources, creating a more sustainable and technologically advanced agriculture industry.

Smart irrigation system is an automatic irrigation and monitoring system on agricultural land with a sensor, automation, and control technology based on the Internet of Things (IoT). This system can reduce the agricultural activities that were previously performed manually into an automatic system with a reduced human supervision. Smart Irrigation systems that are widely developed used Arduino as the controller. Arduino still lacks in response, low durability, and sensitivity to temperature change, hence requiring frequent maintenance to avoid weather disturbances, insects, and others. This paper presents a development of a smart irrigation system using a Programmable Logic Controller (PLC) as the controller and a soil moisture sensor as a humidity condition measurement tool. The advantage of using PLC as a controller is more stable and has sensor compatibility with higher accuracy. Hence the results are more consistent and accurate. The PLC system is expandable, allowing for the inclusion of more channels for sensors and other measurement instruments. The developed system can collect data on soil moisture conditions, trigger valves, and perform auto irrigation using sprinklers, reducing or even eliminating the need for human intervention. The IoT collects data from sensors and updates the data into a database system, allowing users to monitor the land conditions in real-time. The developed system was predicted to save manpower (20%) and water usage (42.47%) compared to the conventional method. Keywords: Smart Irrigation; IoT; PLC; Moisture Sensor; Sprinkler

In Tanzania, almost 30% of the farm land are practicing traditional irrigation farming while around 60% rely on the seasonal rains which are only once every year. This resulted to inefficiency agriculture practices due to the absence of real-time weather data that in cooperates plants characteristics on seasonal growth for better yield. Studies have shown that, only about 10% of the crop caltivated land in Tanzania are farming using modern irrigation practices which include drip and smart irrigation systems. To address these challenges for the purpose of improving crop yield, there is a need to research, design and develop an integrated farming system that will monitor crop environmental conditions and nutritional requirements for the purpose of improving harvest and reduce food shortages. Based on this gap, the current research is aiming to design and develop a smart drip irrigation and fertigation system, using Internet of Things (IoT) technology. Due to the availability of many crops in Tanzania, this study will specifically focusing on tomato farming because they are commonly used as food crop as well cash crops in many parts of Tanzania. This innovative idea integrates sensors and real-time data analysis capabilities to enhance precision in water conservation and nutrient management. Studies have shown that tomato crops thrive best in the temperature range between 20 and 30 ℃ with humidity content above 60% and soil pH value between 6.2 and 6.8. This suitable weather condition for tomato growth is available in many parts of the Tropical countries like Tanzania. The implementation of this research project is based on design and develop a prototype for smart drip irrigation and fertigation system to be used for small and medium farmers in Tanzania. The culmination of these efforts aims to modernize Tanzanian agriculture by improving the efficiency and sustainability of farming practices. The project underscores the significance of precision agriculture techniques in optimizing crop yield and resource utilization. It emphasizes the potential of IoT—driven solutions in addressing longstanding agricultural challenges. The developed of a smart irrigation and fertigation system not only offers a promising avenue for enhancing agricultural productivity but also contributes to environmental conservation efforts through more efficient resource management.

The role of the Internet of Things in Healthcare in supporting clinicians and patients: A narrative review

Objective: This study presents a novel concept of an efficient and smart irrigation system for supporting the farmer’s communities using an Internet of Things (IoT) and to overcome the loss from their cultivation a smart monitoring system is incorporated. Methods: This system is classified into two different phases. In first phase, the irrigation water storage tank will be controlled by the smart irrigation system. The level of the water is maintaining by the water level manger (sensor) and if the maximum level is decreased then it fills the water automatically with the support of the controller. However, this process is functioning under the approval of the farmer in every stage. The humidity of soil is observing based on the plants and the water will be supplied if it needs in the second phase. The decisions will be taken by the decision maker with the support of other co-devices and it has been monitored by the concern farmer and reported periodically in this process. In case, the soil threshold value is overcoming then the decision maker will be activated. The irrigation tank water level is maintaining perfectly by the proposed system without the farmer presences in the field and it is designed especially for managing discontinues electricity situation. Findings: The fault ratio is less than 1% and it occurs due to the device failures. The threshold value has been set based on the cultivated plants for maintaining the humidity of soil and it differs according the plants. The agri-cloud is providing the needed information at right time and it inculcates required nutrient for the high yields to the farmers. This system can be applied for all the plants. Application: Therefore every farmer can be benefited from their cultivation, leads to save the cost, guides to get high yields, provides the platform for getting 100% of the profit without third parties participations offers an awareness and neediness for making an organic based cultivation and help to avoid the loss or failures. Keywords: Agriculture, Cloud Sever, Internet of Things, Smart Irrigation, Wireless Sensors

The development of the Internet of Things (IoT) and machine learning (ML) technologies has triggered smart agricultural systems. In smart agriculture, irrigation management plays a major role to reduce water waste. The monitoring settings, hardware modules, communication technology, and storage systems used in smart irrigation systems were analyzed to determine the optimal nature of water flow. This assessment aims to give an overview of the current state of the irrigation system by taking into account weather and soil moisture. This paper provides a comprehensive review of the utilization of various hardware modules in smart irrigation systems. Moreover, various communication technologies that aid in data transfer for efficient smart irrigation are reviewed. The ML method used for prediction is also evaluated, as well as based storage technologies like the cloud and databases used to store data for predictive irrigation systems. As a result, the paper provides an overview of all the factors that contribute to irrigation systems’ smart operation as well as potential future paths for improving agricultural systems through IoT.

Information technology has become one of the most important infrastructure components of virtually any organization. Although information technology has a crucial impact on the success of organizations it is reported that IT projects have rather high failure rates. Therefore, it is vitally important for organizations to improve the performance and success rates of IT projects. However, the reasons for failures are versatile and an ongoing very active fields of research especially in information systems and management. An established approach to evaluate IT projects is to define relevant so called critical success factors and analyze IT projects according to these criteria. This analysis is often of a qualitative nature. The objective of our paper is to enrich the analysis of critical success factors by alternative methods in particular rough set theory. We motivate the usage of rough sets to further improve the analysis of critical success factors with the goal to better manage IT projects and increase their success rate.KeywordsUncertaintySoft ComputingRough SetsIT Project ManagementCritical Success Factors

The purpose and objective of this research are to analyze project success factors in the Information technology sector in Bosnia and Herzegovina. Methods that were used during the research were conditioned by the problematics that are the subject of the research. The conducted research of critical success factors is quantitative. The research construct of project success influenced by critical success factors is tested. Necessary information about critical success factors was gathered using a questionnaire. During the results analysis phase for reliability and validity testing Confirmatory Factor Analysis was used, and for hypothesis testing the Structural equation modeling. Results of the research showed that the critical factors for IT project success in Bosnia and Herzegovina are competent project managers, technical background, project team, organizational support, and stakeholders. This research represents the first analysis of critical success factors for projects in the IT industry in Bosnia and Herzegovina. The limitation of this research is a smaller sample of examinees. This is the result of insufficient development of the IT industry and project management in Bosnia and Herzegovina.

A CASE tool to support critical success factors analysis in IT planning and requirements determination

PurposeEffective information security management is a strategic issue for organizations to safeguard their information resources. Strategic value alignment is a proactive approach to manage value conflict in information security management. Applying a critical success factor (CSF) analysis approach, this paper aims to propose a CSF model based on a strategic alignment approach and test a model of the main factors that contributes to the success of information security management.Design/methodology/approachA theoretical model was proposed and empirically tested with data collected from a survey of managers who were involved in decision-making regarding their companies’ information security (N = 219). The research model was validated using partial least squares structural equation modeling approach.FindingsOverall, the model was successful in capturing the main antecedents of information security management performance. The results suggest that with business alignment, top management support and organizational awareness of security risks and controls, effective information security controls can be developed, resulting in successful information security management.Originality/valueFindings from this study provide several important contributions to both theory and practice. The theoretical model identifies and verifies key factors that impact the success of information security management at the organizational level from a strategic management perspective. It provides practical guidelines for organizations to make more effective information security management.

Logistics 4.0 is a concept related to Industry 4.0, encompassing skills and notions of supply chain organization, integrating logistics with advanced technology in order to satisfy consumer demand for customized goods and services. Industry 4.0 is transforming businesses and supply chains through advanced technologies like analytics, big data, Internet of things, and cyber-physical systems, enhancing warehousing, manufacturing, and logistics. Logistics 4.0 can be regulated by properly analyzing specific Critical Success Factors using a Multi-Criteria Decision Making model in uncertain or ambiguous circumstances. Hence, it is necessary to explore the CSFs while bringing logistics 4.0 into action. These CSFs are interlinked, and this interlinkage is examined through the D-number-based Pythagorean fuzzy Decision Making Trial and Evaluation Laboratory method, which is suitable for group decision-making in incomplete and uncertain data. The proposed research paradigm incorporates the abilities of Trapezoidal Pythagorean Fuzzy Numbers for dealing with fuzziness and D-Numbers for getting an improved and further precise decision from a heterogeneous group of decision-makers using their linguistic choices. Additionally, it is adaptive and versatile in managing the intrinsic uncertainty brought on by ambiguous and subjective information.

Data cryptography in the Internet of Things using the artificial bee colony algorithm in a smart irrigation system