Performance Evaluation of Long Range (LoRa) Wireless RF Technology blue for the Internet of Things (IoT) Using Dragino LoRa at 915 MHz

Internet of Things (IoT) is a developing concept that introduces the network of physical sensors which are interconnected to each other. Some sensors are wirelessly connected among themselves and to the internet. Currently, IoT applications demand substantial requirements in terms of Radio Access Network (RAN) such as long-range outdoor coverage, environmental factors, obstructions, interference, power consumption, and many others. Also, the current wireless technologies are not able to satisfy all these requirements simultaneously. Therefore, there is no single wireless standard that would predominate the IoT. However, one relevant wireless radio solution to IoT is known as Long Range Wide Area Network (LoRaWAN), which is one of the Low Power Wide Area Network (LPWAN) technologies. LPWAN has appeared as a significant solution to offer advantages such as long-range coverage connectivity with low power consumption, an unlicensed spectrum, and affordability. Most likely LoRa with the inherent long-range coverage and low power consumption features will become the “go-to” technology for IoT applications. For that reason, the proposed research entails the performance evaluation of LoRa IoT application under different scenarios at the University of the North Florida campus. Each scenario includes dynamic and static tests that focus on performance evaluation of the LoRaWAN physical-layer, such as different configurations, coverage range, strength and quality indicators (RSSI and SNR respectively), test schedules, and environmental factors. This application will involve connecting to different IoT servers in the cloud, such as The Things Network (TTN), Amazon Web Services (AWS), integration with Cayenne

Extracting reaction systems from function behavior

Reaction systems, introduced by Ehrenfeucht and Rozenberg, are a theoretical model of computation based on the two main features of biochemical reactions: facilitation and inhibition, which are captured by the individual reactions of the system. All reactions, acting together, determine the global behavior or the result function, res, of the system. In this paper, we study decomposing of a given result function to find a functionally equivalent set of reactions. We propose several approaches, based on identifying reaction systems with Boolean functions, Boolean formulas, and logic circuits. We show how to minimize the number of reactions and their resources for each single output individually, as a group, and when only a subset of the states are considered. These approaches work both when the reactions of the given res function are known and not known. We characterize the minimal number of reactions through the minimal number of logical terms of the Boolean formula representation of the reaction system. Finally, we make applications recommendations for our findings

Piece-wise constant models for RFID traffic

Available security standards for RFID networks (e.g. ISO/IEC 29167) are designed to secure individual tag-reader sessions and do not protect against active attacks that could also compromise the system as a whole (e.g. tag cloning or replay attacks). Proper traffic characterization models of the communication within an RFID network can lead to better understanding of operation under \u27normal\u27 system state conditions and can consequently help identify security breaches not addressed by current standards. We consider the adaptation of two known piece-wise linear models for the purposes of modeling RFID command arrivals at a reader: Bayesian Blocks and Knuth\u27s rule. Our preliminary results indicate that both methods could potentially be used to detect changes in system state (e.g. changes in the rate of command arrivals at a reader)

Developing serious games to promote cognitive abilities for the elderly

This paper presents the design of a computerized serious game suite called the \u27Smart Thinker\u27, which is used to enhance core cognitive skills. The focus is specifically on memory and attention skills. Smart Thinker empowers older adults to exercise their brains and achieve their maximum cognitive performance. To achieve this objective, a thorough study was completed on 59 older adults who were randomly separated as participants of a controlled group or an intervention group. The 20 participants within the controlled group did not play Smart Thinker and were not surveyed. The Mini Mental State Examination (MMSE) was administered to both groups at the beginning and ending of the six week period. The measuring tool was administered under the guidance of licensed clinical social workers of the Alzheimer\u27s Project and was used to determine whether Smart Thinker had an effect on the participants\u27 cognitive functioning. This game research revealed a significant improvement in the cognitive skills of the intervention group who used Smart Thinker Game compared to the controlled group who did not play Smart Thinker

Regulations and standards aware framework for recording of mhealth app vulnerabilities

The authors describe a standards-based security framework for the purposes of recording security and privacy vulnerabilities discovered in mHealth apps. The proposed framework is compliant with the international standard for software architecture descriptions, ISO/IEC/IEEE 42010, relevant state-agency regulations, and US federal healthcare mandates, as well as computing standards for data interchange formats. Future real-life implementations are envisioned to consists of three key components: (1) design and implementation of a repository that links vulnerabilities to concepts from the taxonomy used by legislative and standardization bodies; (2) population of the repository with security vulnerability descriptions that follow a standard format, such as JavaScript Object Notation (JSON); and (3) implementation of a searchable user interface (e.g., Google’s Firebase UI), which allows for aggregation statistics, data analytics, as well as public access to the repository. The proposed framework design promotes timely updates of regulations, standardization drafts, and app development platforms

Safe Route: A Mobile App-Based Intelligent and Personalized Fire Evacuation System

Project of Merit Winner All modern buildings have fire evacuation protocols, the most common of which are exit signs to the nearest exit. However, these simple protocols ignore the possibility of unsafe paths and unexpected fire hazards. The goal during fire evacuations is to escape safely and efficiently, but this can be difficult without knowing which routes are safest. A mobile application called Safe Route was created at the University of North Florida (UNF) to provide building occupants with a personalized fire evacuation route helping them to efficiently navigate to the safest exit. Bluetooth Low Energy (BLE) beacons were utilized for the indoor positioning system (IPS) and the network topology that includes a Long Range Wide Area Network (LoRaWAN) infrastructure. A graph network of routes and nodes was designed based upon the provided floor plan of Building 4 at UNF and linked with a routing algorithm to determine the safest route. A safety score was calculated based upon a variety of parameters including temperature, fire growth rate, and carbon dioxide concentration, among others. Dijkstra’s algorithm was then implemented to determine the evacuation route with the best total safety score. Recent tests of Safe Route suggest that evacuation route optimization is effective, and the navigation assistance is accurate. The IPS is still in development to ensure its robustness, and future researchers could continue to improve the associated IPS algorithm. Researchers could also consider commercializing Safe Route or making it open-source for use in fire evacuations anywhere in the world

Performance of BFSA Collision Resolution: RFID Including Non-unique Tag IDs

As RFID technology becomes ever more affordable, its large scale implementation has been a growing trend in recent years. While current protocols allow for non-unique tag IDs, most existing implementations largely optimize RFID system’s performance based on the assumption of unique tag IDs and treat the existence of non-unique tag IDs within reader’s range as a rare occurrence. Nevertheless, unless formally evaluated, it is not clear, what is the degree of performance degradation in the presence of non-unique tag IDs .We evaluate the behavior of Basic Frame Slotted ALOHA (BFSA) collision resolution for an RFID system using OPNET Modeler 14.5 as both simulation, as well as, analytical results visualization platform. The system is built assuming muting of tags by the reader and contains a mix of unique and non-unique tag IDs. Our findings are compared with results obtained from the evaluation of a similar model for a system consisting solely of unique tag IDs . The comparison of total census delay and throughput under variable frame sizes showed an increase in total census delay with an increase in number of tags and a decrease in network throughput with increase in the number of tags for the system allowing non-unique IDs

Determining predisposition to insider threat activities by using text analysis

Insider threats are difficult to deal with because employees in any organization have a certain level of access to the company\u27s secure network which bypasses the external security measures such as firewalls that have been put in place to protect the organization. The goal of this paper is to design and implement a predictive model which uses linguistic analysis as well as K-means to determine an employee\u27s risk level computer-mediated communication specifically emails and related social networking. Computer-mediated communication (CMC) is a form of communication over virtual spaces where users cannot see each other\u27s face. CMC includes email and communication over social networks, amongst others. This will be accomplished by determining whether or not employees meet certain personality criteria which establish how much of a risk they pose to their employers. In this study, various datasets are used including a real-world case study as a test bed for designed algorithm and tested results