Internet of Things – ICIOT 2019

In underground (UG) multiple-input and multiple-output (MIMO), the transmit beamforming is used to focus energy in the desired direction. There are three different paths in the underground soil medium through which the waves propagates to reach at the receiver. When the UG receiver receives a desired data stream only from the desired path, then the UG MIMO channel becomes three path (lateral, direct, and reflected) interference channel. Accordingly, the capacity region of the UG MIMO three path interference channel and degrees of freedom (multiplexing gain of this MIMO channel requires careful modeling). Therefore, expressions are required derived the degrees of freedom of the UG MIMO interference channel. The underground receiver needs to perfectly cancel the interference from the three different components of the EM-waves propagating in the soil medium. This concept is based upon reducing the interference the undesired components to minimum at UG receiver using the receive beamforming. In this paper, underground environment aware MIMO using transmit and receive beamforming has been developed. The optimal transmit beamforming and receive combining vectors under minimal inter-component interference constraint are derived. It is shown that UG MIMO performs best when all three component of the wireless UG channel are leveraged for beamforming. The environment aware UG MIMO technique leads to three-fold performance improvements and paves the wave for design and development of next generation sensor-guided irrigation systems in the field of digital agriculture.

Video is by far the “biggest” Big Data, stretching network and storage capacity to their limits. To handle the situation, video compression has been an active field of study for many years, producing output of huge commercial interest, e.g., MPEG-2 and DVD. However, video coding is a computationally expensive process and for this reason, parallelization was proposed at various granularity levels. Of particular interest, are block level methods implemented in HEVC (High Efficiency Video Coding) which was designed to be the successor of H.264/AVC for the 4K era. Parallelization in HEVC is supported by the following three modes: slices, tiles and wavefront. While considerable research was conducted on the parallelization options of HEVC, it was focused on the case of homogeneous processors. In this paper we consider video coding parallelization when the processing elements are heterogeneous. In particular, we focus on wavefront and tile parallelism and measure the performance of scheduling schemes for the induced subtasks. Through simulation experiments with dataset values obtained from common benchmark sequences, we conclude on the relevant merits of the evaluated scheduling algorithms.

An unsecured or weak authentication system between an IoT device and a user provides opportunities to attackers to manipulate and use the IoT device as botnet. The proliferation of IoT devices with an unsecured/weak authentication mechanism has increased the threat of using a huge number of IoT devices as botnets for large-scale DDoS attacks. Default credential pairs (like ‘root-root’ or ‘admin-admin’) for the Telnet or SSH connections are still part of a large group of IoT products, and many malwares have exploited this vulnerability to capture a large number of IoT devices and use them as botnets. In the recent past, Mirai malware had infected roughly a million IoT devices at its peak by brute-forcing just 62 pairs of default credentials. In this paper, we present a concept called ‘login puzzle’ to prevent capture of IoT devices in a large scale. Login puzzle is a variant of client puzzle, which presents a puzzle to the remote device during the login process to prevent unrestricted log-in attempts. Login puzzle is a set of multiple mini puzzles with a variable complexity, which the remote device is required to solve before logging into any IoT device. Every unsuccessful log-in attempt increases the complexity of solving the login puzzle for the next attempt. In this paper, we have introduced a novel mechanism to change the complexity of puzzle after every unsuccessful login attempt. If each IoT device had used login puzzle, Mirai attack would have required almost two months to acquire devices, while it acquired them in 20 h.

Internet of Things (IoT) devices, expected to increase exponentially over the next several years, are easy targets for attackers. To make these devices more secure, the IETF’s draft of Manufacturer Usage Description (MUD) provides a means for the manufacturer of an IoT device to specify its intended purpose and communication patterns in terms of access control lists (ACLs), thereby defining the device’s normal behaviour. However, MUD may not be sufficient to comprehensively capture the normal behaviour specification, as it cannot incorporate variable operational settings that depend on the environment. Further, MUD only supports limited features. Our approach overcomes these limitations by allowing the administrator to define the normal behaviour by choosing combinations from a wider set of features that includes physical layer parameters, values of packet headers, and flow statistics. We developed and implemented a learning-based system that captures and demodulates wireless packets from IoT devices over a period of time, extracts the features specified in the normal behaviour specification, and uses a learning algorithm to create a normal model of each device. Our implementation also enforces these normal models by detecting violations and taking appropriate actions, in terms of ACLs on an Internet Gateway, against the misbehaving devices. Hence, our framework makes the specification tighter and clearer than what is possible with MUD alone, thereby making IoT systems more secure.

In the Internet of Things (IoT), billions of physical devices, distributed over a large geographic area, provide a near real-time state of the world. These devices’ capabilities can be abstracted as IoT services and delivered to users in a demand-driven way. In such a dynamic large-scale environment, a service provider who supports a service level agreement (SLA) can have a comprehensive competitive edge in terms of service quality management, service customization, optimized resource allocation, and trustworthiness. However, there is no consistent way of drafting an SLA with respect to describing heterogeneous IoT services, which obstructs automatic service selection, SLA negotiation, and SLA monitoring. In this paper, we propose an ontology, WIoT-SLA, to achieve semantic interoperability. We combine IoT service properties with two prominent web service SLA specifications: WS-Agreement and WSLA, to take advantage of their complementary features. This ontology is used to formalize the SLAs and SLA negotiation offers, which further facilitates the service selection and automatic SLA negotiation. It can also be used by a monitoring engine to detect SLA violations by providing the semantics of service level objectives (SLOs) and quality metrics. To evaluate our work, a prototype is implemented to demonstrate its feasibility and efficiency.

Fault detection and notification in the distribution lines are very important for the operation of the power system. Due to the high cost of communication technology, largely rural area, and so many points of sensor installation, there are limited and difficult to monitoring and data sending. In this paper, we proposed concept using wireless sensor networks that could sense the faulty event in the distribution line, display to the web application as well as send an alarm notification to area distribution dispatching center and service crew, by LoRa network that a low cost, low power, and long-range communication via IoT.

This paper presents the design and implementation of an IoT-based system for window energy management. The system computes thermal transmittances of window units and solar heat gain coefficients through window units from measured sensor readings. It is critical to have energy efficient windows in homes and offices so as to conserve energy. In order to test the performance of the window units in realistic environments we created a system which can be used outdoors at any time. It is convenient for a user to control the system and access the measured data from a remote or even mobile site. The goal of this work was to design and implement a system that measures sensor data, transmits the data over a wireless communication link, distributes the data through the Internet, and stores the data in a database for analysis at any time and anywhere. The IoT is a computer network, in which anyone and anything can connect together anytime and anywhere [1]. It is realizable through sensing and communication technologies [2]. The IoT approach was adopted to achieve our goal due to the availability of sensing technology, wireless communication technologies, and standard computer networking protocols. We designed and implemented a system for calculating the thermal energy related parameters of the window units. The measured data from sensors were transmitted to a cloud server over cellular networks and the Internet. The data in the server can be accessed, stored, and displayed remotely. As long as electricity and cellular phone networks are available, the system can connect sensors to users. Extensive testing was conducted to verify the operation of the system. The testing and measurement results show that the system successfully performs the necessary operations to achieve the goal.

End-mill damage causes the losses of surface smooth and dimensional accuracy for the machined part. In addition, offline monitoring of the end-mill conditions causes downtime and consequently reduce productive efficiency. In order to sense and monitor the conditions of end-mill in real time, an intelligent Internet of Things (IoT) system dedicated to online conditions monitoring of end-mill has been developed in this research work. The designed smart holder highly integrated with triaxial acceleration sensor, Micro Controller Unit (MCU), wireless radio chip and battery is demonstrated. The system collects high resolution end-milling data during cutting without interfering with the machining process. In order to extract the data sequence containing the information highly related to the conditions of the end-mill, a simple but effective data extraction algorithm based on sinusoidal correlation is proposed. By real-time exploring the extracted data sequence via the developed data mining algorithm on the Computerized Numerical Control (CNC) edge server, the conditions of end-mill can be monitored online and consequently decision can be made in real time.

Enterprise IoT is an advanced extension of Internet of Things (IoT) that enables intelligent enterprise systems. It focuses on connecting the enterprise assets and their devices with backend application services and frontend user interactions. While it is more complicated and more impactful than smart home, it faces several challenges such as a large number of IoT devices deployed at various locations and also multiple users to be granted with different permissions. To solve these challenges, we propose a multi-domain enterprise IoT system in consideration of both user movement and IoT device relocation. We propose a context-aware continuous authentication method to authenticate mobile users to the IoT domains based on the context inferred from various sensors on the smartphones and in the IoT domains. We also propose a dynamic device pairing method to support the mobility of users and IoT devices based on data (e.g., contexts, access history, etc.) sharing among the IoT domain, the enterprise server, and the mobile users.

Unfortunately, many deaths are reported every year during the summer for infants, kids and pets who were left in cars and suffered from heatstroke. This paper is proposing a simple smart IoT system for in car detection of a living subject and taking the necessary actions to prevent their life loss. The system has a wide range of sensors including microwave sensors to collect a large set of data inside the car. The system will analyze the data and make the appropriate actions to prevent any death. These actions include sending an alert message to the parents and the emergency department, rolling down the windows, or starting the engine and turning on the air conditioner.

Growing cities always have parking challenges and they are in need for creative ideas to solve this issue and avoid the time wasted in searching for empty parking spots. To overcome the problem, this paper proposes a simple solution using a low-cost cloud-based system design. The design will be initially implemented on campus in one parking lot at the University of Central Oklahoma. The goal is to make the faculties and students life easier by guiding them to empty parking spots. The design of the proposed system is discussed in this paper and preliminary data are presented including the cost function. The system will guide the users through the web-based application.