The surge in global population is compelling a shift toward smart agriculture practices. This coupled with the diminishing natural resources, limited availability of arable land, increase in unpredictable weather conditions makes food security a major concern for most countries. As a result, the use of Internet of Things (IoT) and data analytics (DA) are employed to enhance the operational efficiency and productivity in the agriculture sector. There is a paradigm shift from use of wireless sensor network (WSN) as a major driver of smart agriculture to the use of IoT and DA. The IoT integrates several existing technologies, such as WSN, radio frequency identification, cloud computing, middleware systems, and end-user applications. In this paper, several benefits and challenges of IoT have been identified. We present the IoT ecosystem and how the combination of IoT and DA is enabling smart agriculture. Furthermore, we provide future trends and opportunities which are categorized into technological innovations, application scenarios, business, and marketability.

An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges

Internet of things (IoT) is a promising technology which provides efficient and reliable solutions towards the modernization of several domains. IoT based solutions are being developed to automatically maintain and monitor agricultural farms with minimal human involvement. The article presents many aspects of technologies involved in the domain of IoT in agriculture. It explains the major components of IoT based smart farming. A rigorous discussion on network technologies used in IoT based agriculture has been presented, that involves network architecture and layers, network topologies used, and protocols. Furthermore, the connection of IoT based agriculture systems with relevant technologies including cloud computing, big data storage and analytics has also been presented. In addition, security issues in IoT agriculture have been highlighted. A list of smart phone based and sensor based applications developed for different aspects of farm management has also been presented. Lastly, the regulations and policies made by several countries to standardize IoT based agriculture have been presented along with few available success stories. In the end, some open research issues and challenges in IoT agriculture field have been presented.

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A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming

textThe order batching problem (OBP) is the problem of determining the number of orders to be picked together in one picking tour. Although various objectives may arise in practice, minimizing the average throughput time of a random order is a common concern. In this paper, we consider the OBP for a 2-block rectangular warehouse with the assumptions that orders arrive according to a Poisson process and the method used for routing the order-pickers is the well-known S-shape heuristic. We first elaborate on the first and second moment of the order-picker's travel time. Then we use these moments to estimate the average throughput time of a random order. This enables us to estimate the optimal picking batch size. Results from simulation show that the method provides a high accuracy level. Furthermore, the method is rather simple and can be easily applied in practice.

https://repub.eur.nl/pub/1810/ERS 2004 098 LIS.pdf

Travel Time Estimation and Order Barching in a 2-Block Warehouse

Internet of Things (IoT) constitutes the next step in the field of technology, bringing enormous changes in industry, medicine, environmental care, and urban development. Various challenges are to be met in forming this vision, such as technology interoperability issues, security and data confidentiality requirements, and, last but not least, the development of energy efficient management systems. In this paper, we explore existing networking communication technologies for the IoT, with emphasis on encapsulation and routing protocols. The relation between the IoT network protocols and the emerging IoT applications is also examined. A thorough layer-based protocol taxonomy is provided, while how the network protocols fit and operate for addressing the recent IoT requirements and applications is also illustrated. What is the most special feature of this paper, compared to other survey and tutorial works, is the thorough presentation of the inner schemes and mechanisms of the network protocols subject to IPv6. Compatibility, interoperability, and configuration issues of the existing and the emerging protocols and schemes are discussed based on the recent advanced of IPv6. Moreover, open networking challenges such as security, scalability, mobility, and energy management are presented in relation to their corresponding features. Lastly, the trends of the networking mechanisms in the IoT domain are discussed in detail, highlighting future challenges.

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Network Protocols, Schemes, and Mechanisms for Internet of Things (IoT): Features, Open Challenges, and Trends

It is essential to increase the productivity of agricultural and farming processes to improve yields and cost-effectiveness with new technology such as the Internet of Things (IoT). In particular, IoT can make agricultural and farming industry processes more efficient by reducing human intervention through automation. In this study, the aim to analyze recently developed IoT applications in the agriculture and farming industries to provide an overview of sensor data collections, technologies, and sub-verticals such as water management and crop management. In this review, data is extracted from 60 peer-reviewed scientific publications (2016-2018) with a focus on IoT sub-verticals and sensor data collection for measurements to make accurate decisions. Our results from the reported studies show water management is the highest sub-vertical (28.08%) followed by crop management (14.60%) then smart farming (10.11%). From the data collection, livestock management and irrigation management resulted in the same percentage (5.61%). In regard to sensor data collection, the highest result was for the measurement of environmental temperature (24.87%) and environmental humidity (19.79%). There are also some other sensor data regarding soil moisture (15.73%) and soil pH (7.61%). Research indicates that of the technologies used in IoT application development, Wi-Fi is the most frequently used (30.27%) followed by mobile technology (21.10%). As per our review of the research, we can conclude that the agricultural sector (76.1%) is researched considerably more than compared to the farming sector (23.8%). This study should be used as a reference for members of the agricultural industry to improve and develop the use of IoT to enhance agricultural production efficiencies. This study also provides recommendations for future research to include IoT systems' scalability, heterogeneity aspects, IoT system architecture, data analysis methods, size or scale of the observed land or agricultural domain, IoT security and threat solutions/protocols, operational technology, data storage, cloud platform, and power supplies.

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Adoption of the Internet of Things (IoT) in Agriculture and Smart Farming towards Urban Greening: A Review

China is a large agricultural country with the largest population in the world. This creates a high demand for food, which is prompting the study of high quality and high-yielding crops. China's current agricultural production is sufficient to feed the nation; however, compared with developed countries agricultural farming is still lagging behind, mainly due to the fact that the system of growing agricultural crops is not based on maximizing output, the latter would include scientific sowing, irrigation and fertilization. In the past few years many seasonal fruits have been offered for sale in markets, but these crops are grown in traditional backward agricultural greenhouses and large scale changes are needed to modernize production. The reform of small-scale greenhouse agricultural production is relatively easy and could be implemented. The concept of the Agricultural Internet of Things utilizes networking technology in agricultural production, the hardware part of this agricultural IoT include temperature, humidity and light sensors and processors with a large data processing capability; these hardware devices are connected by short-distance wireless communication technology, such as Bluetooth, WIFI or Zigbee. In fact, Zigbee technology, because of its convenient networking and low power consumption, is widely used in the agricultural internet. The sensor network is combined with well-established web technology, in the form of a wireless sensor network, to remotely control and monitor data from the sensors.In this paper a smart system of greenhouse management based on the Internet of Things is proposed using sensor networks and web-based technologies. The system consists of sensor networks and asoftware control system. The sensor network consists of the master control center and various sensors using Zigbee protocols. The hardware control center communicates with a middleware system via serial network interface converters. The middleware communicates with a hardware network using an underlying interface and it also communicates with a web system using an upper interface. The top web system provides users with an interface to view and manage the hardware facilities ; administrators can thus view the status of agricultural greenhouses and issue commands to the sensors through this system in order to remotely manage the temperature, humidity and irrigation in the greenhouses. The main topics covered in this paper are:1. To research the current development of new technologies applicable to agriculture and summarizes the strong points concerning the application of the Agricultural Internet of Things both at home and abroad. Also proposed are some new methods of agricultural greenhouse management.2. An analysis of system requirements, the users’ expectations of the system and the response to needs analysis, and the overall design of the system to determine it’s architecture.3. Using software engineering to ensure that functional modules of the system, as far as possible, meet the requirements of high cohesion and low coupling between modules, also detailed design and implementation of each module is considered.

Design of an Intelligent Management System for Agricultural Greenhouses Based on the Internet of Things

Environmental factors are increasingly being considered in supply chain risk management (SCRM), which itself represents a growing trend. Accordingly, dynamic supplier selection and order allocation have become very important. Both qualitative and quantitative factors should be considered in the selection of eligible suppliers. In this study, a novel two-stage comprehensive mathematical model is developed for selecting a set of suppliers and assigning an order quantity to each supplier. The first stage involves a primary selection of alternative suppliers according to the risk value, which is determined using qualitative and quantitative methods based on the best–worst method, and the second stage involves establishing a multiobjective mathematical model for dealing with dynamic supplier selection and order allocation. The proposed approach, which helps enterprises manage uncertainty in SCRM, is applied in this study to the new energy vehicles industry.

A model integrating environmental concerns and supply risks for dynamic sustainable supplier selection and order allocation

Mobile computing provides useful, accurate, and timely information to any customer at any time and any place, which greatly changes the traditional way of reading data in the warehouse. The shelf layout of a warehouse center is one of the important factors affecting the efficiency of operation. Modern distribution centers use the mobile computing technology to store warehouse data, and these new layouts can significantly reduce the order turnover time and cost. This paper focuses on order picking at a storage center, a real-time communication system using data read-write devices, removes the limitation of the picking channel being a straight line and performs the curve design of the main channel of V-shaped and fishbone layouts. Using mobile computing technology, we can obtain the order position in real time and store relevant data, gather the order in time, and reduce the operating costs. Afterward, we built a storage area utilization model with the main channel selected as the curve and a stochastic model of return-type picking path with the main channel as the curve and verified the effectiveness of the mathematical model through simulation using the MATLAB software.

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Design of V-Type Warehouse Layout and Picking Path Model Based on Internet of Things

In this paper, we study the improvement of a storage location strategy through the use of big data technology, including data collection, cluster analysis and association analysis, to improve order picking efficiency. A clustering algorithm is used to categorize the types of goods in orders. Classification is performed based on the turnover of goods, value, sales volume, favorable commodity ratings, whether free shipping is provided and whether cash on delivery is supported. An association algorithm is used to determine the relationships among goods by studying the habits of consumers who buy them. A method for improving the class-based storage strategy is proposed. The picking distance of the improved storage strategy is compared with that of the traditional strategy via simulation experiments. The picking efficiency is shown to be enhanced by the improved strategy.

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Study on a storage location strategy based on clustering and association algorithms

Fruit industry occupies a pivotal position in agricultural production, unsalable fruit is a major issue related to people's livelihood. The research puts forward the construction of e-commerce service platform based on the analysis of the sales status of local fruit. The platform uses the sensor technology to achieve the fruit tree growth environment and the whole process of growth of technical guidance and safety monitoring to facilitate the quality of fruit traceability. The industrialization of local fruit can be achieve through the construction of fruit supply and demand platform to open up fruit network sales channels with Internet thinking and broaden local fruit market.

Li Zhou

Papers

Design of an Intelligent Management System for Agricultural Greenhouses Based on the Internet of Things

A model integrating environmental concerns and supply risks for dynamic sustainable supplier selection and order allocation

Design of V-Type Warehouse Layout and Picking Path Model Based on Internet of Things

Study on a storage location strategy based on clustering and association algorithms

Research on Application of Local Fruit E-Commerce Based on Internet of Things