IoT Technologies in Agricultural Environment: A Survey

Agriculture functions as an indispensable act in the world by meeting one of the basic needs of an individual named food, in spite of the fact that the assets are being reduced day by day and also various other problems arise irrespective of biases. In this scenario, unlike many technologies, when every other way fails to sense the routine of a crop, automation takes place by connecting to the invincible storages like cloud and streamlining the process by figuring its hardware and implementing user-friendly internet platform. IoT has set a benchmark in the technologies and has become a backbone to agriculture. This advancement in technology helps in farming automation, which helps in shaping a farmer’s workspace, ensuring them with device management, connectivity management, and productivity as a result along with remote management. This paper gives an insight on introduction to IoT, agriculture IoT, emerging wireless technologies of IoT, architectures and applications of IoT.

     

A review on evolving domains of Internet of Things: Architecture,applications, and technical challenges

The Internet of Things (IoT) is a system that includes smart items with different sensors, advanced technologies, analytics, cloud servers, and other wireless devices that integrate and work together to create an intelligent environment that benefits end users. With its wide spectrum of applications, IoT is revolutionizing both the current and future generations of the Internet. IoT systems can be employed for broad-ranging real applications, such as agriculture, the environment, cities, healthcare, and the industrial sector. In this paper, we briefly discuss the three-tier architectural view of IoT, its different communication technologies, and the smart sensors. Moreover, we study various application areas of IoT such as the environmental domain, healthcare, agriculture, smart cities, and industrial, commercial, and general aspects. A critical analysis is shown for the existing schemes and techniques related to this work. Further, this paper addresses the basic context, tools and evaluation approaches, future scope, and the advantages and disadvantages of the aforestated IoT applications. A comprehensive analysis is provided for each domain along with its fundamental parameters like the quality of service (QoS), network longevity, scalability, energy efficiency, accuracy, and cost. Finally, this study highlights the technical challenges and open research problems existing in different IoT applications.     

Security and Privacy in IoT: A Survey

The Internet of Things (IoT) is a network of globally connected physical objects, which are associated with each other via Internet. The IoT foresees the interconnection of few trillions of intelligent objects around us, uniquely and addressable every day, these objects have the ability to accumulate process and communicate data about themselves and their surrounding environment. The best examples of IoT systems are health care, building smart city with advance construction management system, public and defense surveillance and data acquisition. Recent advancement in the technology has developed smart and intelligent sensor nodes and RFIDs lead to a large number of wireless networks with smart and intelligent devices (object, or things) connected to the Internet continuously transmit the data. So to provide security and privacy to this data in IoT is a very challenging task, which is to be concerned at highest priority for several current and future applications of IoT. Devices such as smart phone, WSNs and RFIDs etc., are the major components of IoT network which are basically resource constrained devices. Design and development of security and privacy management schemes for these devices is guided by factors like good performance, low power consumption, robustness to attacks, tampering of the data and end to end security. Security schemes in IoT provide unauthorized access to information or other objects by protecting against alterations or destruction. Privacy schemes maintain the right to control about the collected information for its usage and purpose. In this paper, we have surveyed major challenges such as Confidentiality, Integrity, Authentication, and Availability for IoT in a brief manner.

     

Intelligent Contextual Information Collection in Internet of Things

As we are moving towards the internet of things (IoT), a significant growth of stationary and mobile sensing and computing IoT devices continuously generate enormous amounts of contextual information, e.g., environmental data. Contextual information collection, reasoning, and inference plays critical role in IoT. In this paper, we consider the contextual information collection and harvesting problem in which stationary sensing and computing devices (sources), which are incapable to communicate with each other either due to their long distance, or for energy efficiency, or spatially dispersed network, rely on mobile IoT devices (collectors) to ‘drain’ their acquired contextual information. (e.g., generating from IoT applications: smart cities, smart metering, and smart agriculture). At the contact instances with the collectors, sources have to decide whether to deliver the contextual information obtained so far or postpone their delivery for later hitting epochs in an effort to sense fresher (or more critical) contextual information. We rest on the principles of Optimal Stopping Theory and propose an intelligent context collection scheme in IoT environments. We show through simulations with synthetic and real mobility data the effectiveness of our scheme compared to other approaches.     

FreeBW-RPL: A New RPL Protocol Objective Function for Internet of Multimedia Things

Most of the current research has been restricted to scalar sensor data based IoT applications. However, today’s research and development activities rely on multimedia-based services and applications while this kind of applications has several requirements in terms of storage, bandwidth, latency, etc. Furthermore, protocols dedicated to IoT applications have proved their weakness in multimedia environments. Hence, a new paradigm called internet of multimedia things (IoMT) has been proposed to fulfill the requirements of multimedia applications. In this paradigm different multimedia things can interact and cooperate with each other over the Internet. Moreover, IETF ROLL working group standardized an IPv6 routing protocol for low-power and lossy networks (RPL for LLNs) for resource constrained devices. In this paper, we propose an enhanced version of RPL for IoMT called free bandwidth (FreeBW)-RPL in which the sensed data is essentially provided by multimedia devices. FreeBW-RPL protocol proposes a new objective function called FreeBW that takes the FreeBW calculation in the network layer. We set the QoS routing challenge as the amount of the bandwidth while selecting the routing path in order to measure the maximum FreeBW so as to deliver better performance of the multimedia applications. Simulations have been conducted over COOJA simulator. The obtained results proved that our proposal outperforms the basic ones in terms of end-to-end delay, throughput, packet delivery ratio and energy consumption and provides better performance than other protocols.

     

A survey on communication protocols and performance evaluations for Internet of Things

The Internet of Things (IoT) is a large-scale network of devices capable of sensing, data processing, and communicating with each other through different communication protocols. In today's technology ecosystem, IoT interacts with many application areas such as smart city, smart building, security, traffic, remote monitoring, health, energy, disaster, agriculture, industry. The IoT network in these scenarios comprises tiny devices, gateways, and cloud platforms. An IoT network is able to keep these fundamental components in transmission under many conditions with lightweight communication protocols taking into account the limited hardware features (memory, processor, energy, etc.) of tiny devices. These lightweight communication protocols affect the network traffic, reliability, bandwidth, and energy consumption of the IoT application. Therefore, determining the most proper communication protocol for application developers emerges as an important engineering problem. This paper presents a straightforward overview of the lightweight communication protocols, technological advancements in application layer for the IoT ecosystem. The survey then analyzes various recent lightweight communication protocols and reviews their strengths and limitations. In addition, the paper explains the experimental comparison of Constrained Applications Protocol (CoAP), Message Queuing Telemetry (MQTT), and WebSocket protocols, more convenient for tiny IoT devices. Finally, we discuss future research directions of communication protocols for IoT.     

Green IoT: A Short Survey on Technical Evolution & Techniques

The Internet of Things (IoT) embodies the confluence of the virtual & physical world. IoT will play an important role in managing the managing depleting resource such as water, fuel, food, etc. However, to realize these applications enormous IoT devices will communicate with each other. This massive connectivity will directly or indirectly aid in Green House Gas emissions. Hence, to admissibly reduce this environmental impact of IoT, it must be greened in terms of energy consumption. Green IoT will reduce environmental exploitation by slashing carbon emission effectively and thus will help in achieving sustainability of the planet. This paper describes the journey of IoT to Green IoT. Along with this, the survey on recent Green-IoT techniques that will effectively help in reducing required energy consumption is presented. Along with this ability of unmanned aerial vehicle (UAV) technology to provide Green IoT and survey on recent energy-efficient UAV assisted communication is presented. In addition to this, a dual battery enabled Unmanned Aerial vehicle base station, an energy-efficient clustering algorithm, has also been proposed to prolong the battery life.

     

Interoperability in semantic Web of Things: Design issues and solutions

The significant improvement in processing power, communication, energy consumption, and the size of computational devices has led to the emergence of the Internet of Things (IoT). IoT projects raise many challenges, such as the interoperability between IoT applications because of the high number of sensors, actuators, services, protocols, and data associated with these systems. Semantics solves this problem by using annotations that define the role of each IoT element and reduces the ambiguity of information exchanged between the devices. This work presents SWoTPAD, a semantic framework that helps in the development of IoT projects. The framework is designer oriented and provides a semantic language that is more user‐friendly than OWL‐S and WSML and allows the IoT designer to specify devices, services, environment, and requests. Following this, it makes use of these specifications and maps them for RESTful services. Additionally, it generates an automatic service composition engine that is able to combine services needed to handle complex user requests. We validated this approach with two case studies. The former concerns a residential security system and the latter, the cloud application deployment. The average time required for service discovery and automatic service composition corresponds to 72.9% of the service execution time in the case study 1 and 64.4% in the case study 2.     

Machine learning for internet of things data analysis: a survey

Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As these numbers grow and technologies become more mature, the volume of data being published will increase. The technology of Internet-connected devices, referred to as Internet of Things (IoT), continues to extend the current Internet by providing connectivity and interactions between the physical and cyber worlds. In addition to an increased volume, the IoT generates big data characterized by its velocity in terms of time and location dependency, with a variety of multiple modalities and varying data quality. Intelligent processing and analysis of this big data are the key to developing smart IoT applications. This article assesses the various machine learning methods that deal with the challenges presented by IoT data by considering smart cities as the main use case. The key contribution of this study is the presentation of a taxonomy of machine learning algorithms explaining how different techniques are applied to the data in order to extract higher level information. The potential and challenges of machine learning for IoT data analytics will also be discussed. A use case of applying a Support Vector Machine (SVM) to Aarhus smart city traffic data is presented for a more detailed exploration.     

Group and hierarchical key management for secure communications in internet of things

Different devices with different characteristics form a network to communicate among themselves in Internet of Things (IoT). Thus, IoT is of heterogeneous in nature. Also, Internet plays a major role in IoT. So, issues related to security in Internet become issues of IoT also. Hence, the group and hierarchical management scheme for solving security issues in Internet of Things is proposed in this paper. The devices in the network are formed into groups. One of the devices is selected as a leader of each group. The communication of the devices from each group takes place with the help of the leader of the corresponding group using encrypted key to enhance the security in the network. Blom's key predistribution technique is used to establish secure communication among any nodes of group. The hierarchy is maintained such that the security can be increased further, but the delay is increased as it takes time to encrypt at every level of hierarchy. Hence, the numbers of levels of hierarchy need to be optimized such that delay is balanced. Hence, this algorithm is more suitable for delay‐tolerant applications. The performance of the proposed Algorithm is evaluated and is proved to perform better when compared with the legacy systems like Decentralized Batch‐based Group Key Management Protocol for Mobile Internet of Things (DBGK).     

An SDN approach to route massive data flows of sensor networks

With the advent of the Internet of Things (IoT), more and more devices can establish a connection with local area networks and use routing protocols to forward all information to the sink. But these devices may not have enough resources to execute a complex routing protocol or to memorize all information about the network. With proactive routing protocols, each node calculates the best path, and it needs enough resources to memorize the network topology. With reactive routing protocols, each node has to broadcast the message to learn the right path that the packets must follow. In all cases, in large networks such as IoT, this is not an appropriate mechanism. This paper presents a new software‐defined network (SDN)–based network architecture to optimize the resource consumption of each IoT object while securing the exchange of messages between the embedded devices. In this architecture, the controller is in charge of all decisions, and objects only exchange messages and forward packets among themselves. In the case of large networks, the network is organized into clusters. Our proposed network architectures are tested with 1000 things grouped in five clusters and managed by one SDN controller. The tests using OpenDayLight and IoT embedded applications have been implemented on several scenarios providing the ability and the scalability from dynamic reorganization of the end‐devices. This approach explores the network performance issues using a virtualized SDN‐clustered environment which contributes to a new model for future network architectures.     

Energy aware cloud-edge service placement approaches in the Internet of Things communications

In recent years, applying Internet of Things (IoT) applications has significantly increased to facilitate and improve quality of human life activities in various fields such as healthcare, education, industry, economics, etc. The energy aware cloud-edge computing paradigm has developed as a hybrid computing solution to provide IoT applications using available cloud service providers and fog nodes for the smart devices and mobile applications. Since the IoT applications are developed in the form of several IoT services with various quality of service (QoS) metrics which can deploy on the cloud-edge providers with different resource capabilities, finding an efficient placement solution as one of challenging topics to be measured for IoT applications. The service placement issue arranges IoT applications on the cloud-edge providers with various capabilities of atomic services though sufficient different QoS factors to support service level agreement (SLA) contracts. This paper presents a technical analysis on the cloud-edge service placement approaches in IoT systems. The key point of this technical analysis is to identify substantial studies in the service placement approaches which need additional consideration to progress more efficient and effective placement strategies in IoT environments. In addition, a side-by-side taxonomy is proposed to categorize the relevant studies on cloud-edge service placement approaches and algorithms. A statistical and technical analysis of reviewed existing approaches is provided, and evaluation factors and attributes are discussed. Finally, open issues and forthcoming challenges of service placement approaches are presented.     

Data analytics in wireless systems and IoT issues and challenges

The emergence of data engineering along with the support of Online Social Networks is growing by millions every day due to the introduction of wireless systems and Internet of Things. The rapid growth of usage of smart devices helps to create new generation knowledge sharing platforms. Data Analytics has a major role to play in the growth and success of wireless and IoT applications. The growth of data has become exponential and is difficult to analyze. Many researchers depend on the data available on Wireless Systems and IoT for developing new generation services and applications. With the opportunity of information and communication technologies like heterogeneous networking, cloud computing, web services, crowd sensing and data mining, ubiquitous and asynchronous information sharing is feasible. But this also brings out a lot of provocations with respect to conflicting standards, data portability, data aggregation, data distribution, differential context and communication overhead. The smart information and communication technology has changed many features of human lifestyle: personal and work places.     

Reliable and secure data transfer in IoT networks

With the rapid technological improvements in mobile devices and their inclusion in Internet of Things (IoT), secure key management becomes mandatory to ensure security of information exchange. For instance, IoT applications, such as smart health-care and smart homes, provide automated services to the users with less or no user intervention. As these application use user-sensitive data, ensuring their security and privacy should be paramount, especially during the key management process. However, traditional approaches for key management will not suit well in IoT environment because of the inherent resource constraint property of IoT devices. In this paper, we propose a novel distributed key management scheme for IoT ecosystem. The proposed scheme efficiently provides security to IoT devices by delegating most of the resource consuming cryptographic processing to a local entity. This entity coordinates with other peer entities to provide a distributed key as well as an authentication mechanism to network devices. In particular, the proposed scheme exploits the advantages of mobile agents by deploying them in different subnetworks as and when required: (1) to process the cryptography work for the IoT devices, and (2) to act as an local authenticated entity to perform fast authentication process. To verify the effectiveness and correctness of our proposed scheme, we have simulated it in a large IoT scenario and evaluated against relevant metrics that includes user mobility, certification generation time, and communication overhead.

     

DDC-OMDC: Deadline-based data collection using optimal mobile data collectors in Internet of Things

Mobile data collectors (MDCs) are very efficient for data collection in internet of things (IoT) sensor networks. These data collectors collect data at rendezvous points to reduce data collection latency. It is paramount to determine these points in an IoT network to collect data in real time. It is important to consider IoT network characteristics to collect data on a specific deadline. First, the disconnected IoT sensor network is a real challenge in IoT applications. Second, it is essential to determine optimal data collection points (DCPs) and MDCs simultaneously to collect data in real time. In this study, Deadline-based Data Collection using Optimal Mobile Data Collectors (DDC-OMDC) scheme is proposed that aims to collect data in a disconnected network with the optimal number of mobile data collectors in a specific deadline for delay-intolerant applications. DDC-OMDC works in two phases. In the first phase, the optimal number of MDCs is determined to collect data at the optimal data collection points to guarantee one-hop data collection from each cluster. The optimal mobile data collectors are determined using optimal DCPs, data collection stopping time, and a specific deadline. In the second phase, the optimal data collection trajectory is determined for each MDC using the nearest neighbor heuristic algorithm to collect data in real time. The simulation results show that the proposed scheme outperforms in collecting data in real time and determines optimal mobile data collectors and optimal data collection trajectory to collect data in a specific deadline for delay-intolerant applications.     

A web service‐based internet of things framework for mobile resource augmentation

Mobile devices are the primary communication tool in day to day life of the people. Nowadays, the enhancement of the mobile applications namely IoTApps and their exploitation in various domains like healthcare monitoring, home automation, smart farming, smart grid, and smart city are crucial. Though mobile devices are providing seamless user experience anywhere, anytime, and anyplace, their restricted resources such as limited battery capacity, constrained processor speed, inadequate storage, and memory are hindering the development of resource‐intensive mobile applications and internet of things (IoT)‐based mobile applications. To solve this resource constraint problem, a web service‐based IoT framework is proposed by exploiting fuzzy logic methodologies. This framework augments the resources of mobile devices by offloading the resource‐intensive subtasks from mobile devices to the service providing entities like Arduino, Raspberry PI controller, edge cloud, and distant cloud. Based on the recommended framework, an online Repository of Instructional Talk (RIoTalk) is successfully implemented to store and analyze the classroom lectures given by faculty in our study site. Simulation results show that there is a significant reduction in energy consumption, execution time, bandwidth utilization, and latency. The proposed research work significantly increases the resources of mobile devices by offloading the resource‐intensive subtasks from the mobile device to the service provider computing entities thereby providing Quality of Service (QoS) and Quality of Experience (QoE) to mobile users.     

A Framework for Engineering Pervasive Applications Applied to Intra-vehicular Sensor Network Applications

The vehicle sector is one of the most exciting application areas for wireless ad hoc networks and pervasive computing technologies. Vehicles are constantly being equipped with more sensors and devices able to collect real-time data on traffic, vehicle condition, passenger health, and so on. Being a relatively new field of application, this area needs tools and methodologies in order to specify requirements and prototype applications. This paper presents a Framework for Pervasive Applications and describes how it can be customized in the case of Vehicular Applications. The framework consists of a set of software requirements, some metrics, and some middleware services for rapid prototyping pervasive applications. In addition, the paper introduces an ongoing project that aims at granting high-quality on-road transportation services for fragile food (e.g. wine). In particular, its objective is to provide a system able to monitor several conditions, like temperature, humidity, light, shocks, etc., which carried products are subject to during transportation.     

Preface to the Special Topic on Devices and Circuits for Wearable and IoT Systems

The concept of Internet of Things (IoT) was first proposed by MIT Prof.Kevin Ash-ton in 1999.The implementation of IoT was mainly through RFID in its early time.With advanced technology and manufacture,diverse implementation forms ofIoT are becoming possible.Wearable devices,as an essential branch of IoT,will have broad application prospects in health monitoring and intelligent healthcare.     

The IoT Architectural Framework,Design Issues and Application Domains

The challenge raised by the introduction of Internet of Things (IoT) concept will permanently shape the networking and communications landscape and will therefore have a significant social impact. The ongoing IoT research activities are directed towards the definition and design of open architectures and standards, but there are still many issues requiring a global consensus before the final deployment. The paper presents and discusses the IoT architectural frameworks proposed under the ongoing standardization efforts, design issues in terms of IoT hardware and software components, as well as the IoT application domain representatives, such as smart cities, healthcare, agriculture, and nano-scale applications (addressed within the concept of Internet of Nano-Things). In order to obtain the performances related to recently proposed protocols for emerging Industrial Internet of Things applications, the preliminary results for Message Queuing Telemetry Transport and Time-Slotted Channel Hopping protocols are provided. The testing was performed on OpenMote hardware platform and two IoT operating systems: Contiki and OpenWSN.