More than a decade of research in the field of thermal, motion, vibration and electromagnetic radiation energy harvesting has yielded increasing power output and smaller embodiments. Power management circuits for rectification and DC-DC conversion are becoming able to efficiently convert the power from these energy harvesters. This paper summarizes recent energy harvesting results and their power management circuits.

Micropower energy harvesting

The Internet of Things (IoT) is undeniably transforming the way that organizations communicate and organize everyday businesses and industrial procedures. Its adoption has proven well suited for sectors that manage a large number of assets and coordinate complex and distributed processes. This survey analyzes the great potential for applying IoT technologies (i.e., data-driven applications or embedded automation and intelligent adaptive systems) to revolutionize modern warfare and provide beneﬁts similar to those in industry. It identiﬁes scenarios where Defense and Public Safety (PS) could leverage better commercial IoT capabilities to deliver greater survivability to the warﬁghter or ﬁrst responders, while reducing costs and increasing operation efﬁciency and effectiveness. This article reviews the main tactical requirements and the architecture, examining gaps and shortcomings in existing IoT systems across the military ﬁeld and mission-critical scenarios. The review characterizes the open challenges for a broad deployment and presents a research roadmap for enabling an affordable IoT for defense and PS.

https://www.mdpi.com/1424-8220/16/10/1644/pdf

A Review on Internet of Things for Defense and Public Safety.

With the popularity of smart devices and the widespread use of machine learning methods, smart edges have become the mainstream of dealing with wireless big data. When smart edges use machine learning models to analyze wireless big data, nevertheless, some models may unintentionally store a small portion of the training data with sensitive records. Thus, intruders can expose sensitive information by careful analysis of this model. To solve this privacy issue, in this paper, we propose and implement a machine learning strategy for smart edges using differential privacy. We focus our attention on privacy protection in training datasets in wireless big data scenario. Moreover, we guarantee privacy protection by adding Laplace mechanisms, and design two different algorithms Output Perturbation (OPP) and Objective Perturbation (OJP), which satisfy differential privacy. In addition, we consider the privacy preserving issues presented in the existing literatures for differential privacy in the correlated datasets, and further provided differential privacy preserving methods for correlated datasets, guaranteeing privacy by theoretical deduction. Finally, we implement the experiments on the TensorFlow, and evaluate our strategy on four datasets, i.e., MNIST, SVHN, CIFAR-10 and STL-10. The experiment results show that our methods can efficiently protect the privacy of training datasets and guarantee the accuracy on benchmark datasets.

Differential Privacy Preserving of Training Model in Wireless Big Data with Edge Computing

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this article, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.

/pdf/a-survey-and-future-directions-on-clustering-from-wsns-to-41aye5zcep.pdf

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

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.

Security and Privacy in IoT: A Survey

This paper addresses a scenario where a medium sized smart city in an Alliance nation has been struck by disaster. A small, multi-national force is deployed for disaster relief. Situational awareness (SA) is important so that resources, including personnel and supplies, may be prioritized to have the most impact and help those in the most need. This SA can be significantly enhanced via information obtained from Internet of Things (IoT) devices, especially in a smart city environment. This paper, which presents work performed by the NATO IST-147 “Military Applications of Internet of Things” group, explores the potential to exploit smart city IoT capabilities in military operations.

Application of IoT in military operations in a smart city

Disaster recovery operations are extremely challenging and place significant demands on multiple resources, including local and international emergency response personnel, non-governmental organizations, and the military. In the immediate aftermath of a disaster, one of the most pressing requirements is for situational awareness (SA) so that resources, including personnel and supplies, may be prioritized to have the most impact and help those in the most need. As the recovery operations continue, the SA needs to be continuously updated based on changing conditions in the affected areas. There are many sources of information to provide SA, including reporting by the victims of the disaster as well as observations made by responding personnel. In this context, SA can be significantly enhanced via information obtained from Internet of Things (IoT) devices, especially in a smart city environment. This paper explores the potential to exploit Smart City IoT capabilities to help with disaster recovery operations.

Exploiting smart city IoT for disaster recovery operations

Ensuring security in the military applications of IoT is a big challenge. The main reasons for this state of affairs is that the sensor nodes of the network are usually mobile, use wireless links, have a small processing power and have a little energy resources. The paper presents the solution for cryptographic protection of transmission between sensor nodes in the data link layer and for cryptographic protection of data stored in the sensor node resources. For this purpose, the Trusted Platform Module (TPM) was used. The proposed solution makes it possible to build secure and fault tolerant sensor network. The following aspects were presented in the paper: the model of such a network, applied security solutions, analysis of the security in the network and selected investigation results of such a network were presented.

Security techniques for the WSN link layer within military IoT

Some obtained results related to an ongoing project which aims at providing a comprehensive approach for implementation of Internet of Things concept into the military domain are presented. A comprehensive approach to fault diagnosis within the Internet of Military Things was outlined. Particularly a method of fault detection which is based on a network partitioning into clusters was proposed. Also, some solutions proposed for the experimentally constructed network called EFTSN was conducted.

Fault-tolerant techniques for the Internet of Military Things

The paper describes a protocol for secure data transmission in Wireless Sensor Networks (WSN). The essence of the process is to ensure security attributes of data transfer in the data link layer. In the paper a model of network consisting of sensors' domain is described. The domain includes one root node (M node), which is a security authority in the domain, and sensor nodes (S node). The proposed protocol involves the M node initialization, S nodes registration, and data transfer between M node and S nodes. All the data security procedures are supported by the Trusted Platform Module (TPM).

Janusz Furtak

Papers

Application of IoT in military operations in a smart city

Exploiting smart city IoT for disaster recovery operations

Security techniques for the WSN link layer within military IoT

Fault-tolerant techniques for the Internet of Military Things

Secure protocol for wireless communication within internet of military things