我的台灣, 看見心靈的故鄉 =2009林磐聳藝術與設計展

Water management is paramount in countries with water scarcity. This also affects agriculture, as a large amount of water is dedicated to that use. The possible consequences of global warming lead to the consideration of creating water adaptation measures to ensure the availability of water for food production and consumption. Thus, studies aimed at saving water usage in the irrigation process have increased over the years. Typical commercial sensors for agriculture irrigation systems are very expensive, making it impossible for smaller farmers to implement this type of system. However, manufacturers are currently offering low-cost sensors that can be connected to nodes to implement affordable systems for irrigation management and agriculture monitoring. Due to the recent advances in IoT and WSN technologies that can be applied in the development of these systems, we present a survey aimed at summarizing the current state of the art regarding smart irrigation systems. We determine the parameters that are monitored in irrigation systems regarding water quantity and quality, soil characteristics and weather conditions. We provide an overview of the most utilized nodes and wireless technologies. Lastly, we will discuss the challenges and the best practices for the implementation of sensor-based irrigation systems.

https://www.mdpi.com/1424-8220/20/4/1042/pdf

IoT-Based Smart Irrigation Systems: An Overview on the Recent Trends on Sensors and IoT Systems for Irrigation in Precision Agriculture

The Internet of Things (IoT) has become a reality. As the IoT is now becoming a far more common field, the demand for IoT technologies to manage the communication of devices with the rest of the world has increased. The IoT is connecting various individual devices called things and wireless sensor networks is also playing an important role. A thing can be defined as an embedded device based on a micro controller that can transmit and receive information. These devices are extremely low in power, memory, and resources. Therefore, the research community has recognized the importance of IoT device operating systems (OSs). An adequate OS with a kernel, networking, real-time capability, and more can make these devices flexible. This review provides a detailed comparison of the OSs designed for IoT devices on the basis of their architecture, scheduling methods, networking technologies, programming models, power and memory management methods, together with other features required for IoT applications. In addition, various applications, challenges, and case studies in the field of IoT research is discussed.

Internet of Things (IoT) Operating Systems Support, Networking Technologies, Applications, and Challenges: A Comparative Review

The growing demand for food in terms of quality and quantity has increased the need for industrialization and intensification in the agriculture field. Internet of Things (IoT) is a highly promising technology that is offering many innovative solutions to modernize the agriculture sector. Research institutions and scientific groups are continuously working to deliver solutions and products using IoT to address different domains of agriculture. This paper presents a systematic literature review (SLR) by conducting a survey of IoT technologies and their current utilization in different application domains of the agriculture sector. The underlying SLR has been compiled by reviewing research articles published in well-reputed venues between 2006 and 2019. A total of 67 papers were carefully selected through a systematic process and classified accordingly. The primary objective of this systematic study is the collection of all relevant research on IoT agricultural applications, sensors/devices, communication protocols, and network types. Furthermore, it also discusses the main issues and challenges that are being investigated in the field of agriculture. Moreover, an IoT agriculture framework has been presented that contextualizes the representation of a wide range of current solutions in the field of agriculture. Similarly, country policies for IoT-based agriculture have also been presented. Lastly, open issues and challenges have been presented to provide the researchers promising future directions in the domain of IoT agriculture.

Role of IoT Technology in Agriculture: A Systematic Literature Review

A survey on security attacks in VANETs: Communication, applications and challenges

Agriculture is becoming an important growing sector throughout the world due to increasing population. Major challenge in agriculture sector is to improve farm productivity and quality of farming without continuous manual monitoring to meet the rapidly growing demand for food. Apart from increasing population, the climate change is also a big concern in agricultural sector. The purpose of this research work is to propose a smart farming method based on Internet of Things (IoT) to deal with the adverse situations. The smart farming can be adopted which offer high precision crop control, collection of useful data and automated farming technique. This work presents an intelligent agriculture field monitoring system which monitors soil humidity and temperature. After processing the sensed data it takes necessary action based on these values without human intervention. Here temperature and moisture of the soil are measured and these sensed values are stored in ThingSpeak [11] cloud for future data analysis.

IoT Based Intelligent Agriculture Field Monitoring System

Data transmission is one of the major challenges in wireless sensor network (WSN). Different routing protocols have been proposed to save energy during data transmission in WSN. Routing protocols based on data-centric approach are suitable in this context that performs in-network aggregation of data to yield energy saving data dissemination. In this paper we propose a modified version of SPIN protocol named M-SPIN and compare its performance with traditional SPIN protocol using broadcast communication, which is a well known protocol as benchmark. We evaluate the M-SPIN protocol using simulation in TOSSIM environment. We find that, M-SPIN exhibits significant performance gains than traditional SPIN routing.

A modified SPIN for wireless sensor networks

Multiple sinks are deployed in large-scale wireless sensor networks (WSNs) to minimize transmission delay and energy consumption and also to extend the network life time. Since the data collected by sensor nodes are forwarded to the sink, therefore proper placement of sinks has a great impact on the performance of the WSNs. This paper introduces two sink placement strategies and discusses their advantages and disadvantages in comparison with an existing strategy. The two strategies are compared with the Geographic Sink Placement (GSP) [3] strategy which is used as a benchmark. Both GSP and proposed two strategies are implemented and evaluated in a simulation environment. Performances of these strategies are analyzed and analysis results are presented in this paper. It has been observed that the proposed strategies exhibit better performances with respect to energy usage and lifetime in comparison with GSP.

Multiple-sink placement strategies in wireless sensor networks

Managing the ever increasing road traffic congestion due to enormous vehicular growth is a big concern all over the world. Tremendous air pollution, loss of valuable time and money are the common consequences of traffic congestion in urban areas. IoT based Intelligent Transportation System (ITS) can help in managing the road traffic congestion in an efficient way. Estimation and classification of the traffic congestion state of different road segments is one of the important aspects of intelligent traffic management. Traffic congestion state recognition of different road segments helps the traffic management authority to optimize the traffic regulation of a transportation system. The commuters can also decide their best possible route to the destination based on traffic congestion state of different road segments. This paper aims to estimate and classify the traffic congestion state of different road segments within a city by analyzing the road traffic data captured by in-road stationary sensors. The Artificial Neural Network (ANN) based system is used to classify traffic congestion states. Based on traffic congestion status, ITS will automatically update the traffic regulations like, changing the queue length in traffic signal, suggesting alternate routes. It also helps the government to device policies regarding construction of flyover/alternate route for better traffic management.

Intelligent Traffic Congestion Classification System using Artificial Neural Network

Energy consumption is the key design criterion for routing data in wireless sensor Network. Recently the use of multiple sinks instead of single is considered as a research topic for energy saving. The objective is to maximize the network lifetime by reducing distance from source node to sink during data transmission. This paper proposes a network partitioning algorithm based on selection of farthest node from k-Nearest Neighbour Graph. After partitioning, a restricted flooding-based routing protocol is used for data transmission. It is shown that the network lifetime significantly increases in a partitioned network in comparison with a non-partitioned network.

Zeenat Rehena

Papers

IoT Based Intelligent Agriculture Field Monitoring System

A modified SPIN for wireless sensor networks

Multiple-sink placement strategies in wireless sensor networks

Intelligent Traffic Congestion Classification System using Artificial Neural Network

Topology partitioning in wireless sensor networks using multiple sinks