An Experimental Study on Direction Finding of Bluetooth 5.1: Indoor vs Outdoor

The Bluetooth Special Interest Group (Bluetooth SIG) introduced a new feature for highly accurate localization called the Direction Finding in the Bluetooth Core Specification 5.1. Since this new localization feature is relatively new, despite the significant interest of industry and academia in the accurate positioning of Bluetooth devices/tags, there are only a handful of experimental studies conducted to evaluate the performance of the new technology. Furthermore, these experimental works are constrained to only indoor environments or performed with hardware emulation of Bluetooth 5.1 via Universal Software Radio Peripherals (USRPs). In this paper, we perform an experimental study on the positioning accuracy of the direction finding using COTS Bluetooth 5.1 devices in booth indoor and outdoor environments to provide insights on the performance gap under these different experimental settings. Our results demonstrate that the average angular error in an outdoor environment is 0.28 degrees, significantly improving the angular error measured in an indoor environment by 73%. It is also demonstrated that the average positioning accuracy measured in an outdoor environment is 22cm which is 39.7% smaller than that measured in an indoor environment

An IoT fall detection and alert system for elderly persons with stroke and heart attack

Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Electrical and Electronic Engineering, May 2020Abrupt falling of the aged population is a rising concern among other chronic sicknesses faced by older people in the world. Elderly patients are disposed to falling abruptly due to heart-related diseases, muscle weakness, high blood pressure, and balance-related diseases such as labyrinthitis – inflammation of the delicate balance regulating parts of the ear. This project focuses on the design and development of simple, low-cost fall detection, and smart alert system. The system detects the fall of a patient using the device's gyroscopes and accelerometers to send an alert message via mail to the caretaker for immediate intervention. The device also possesses a panic push button that can be used by the patient to call for urgent help. The device's buzzer is used to make an alert sound for caretakers who are around the patient's vicinity to respond urgently. Data collected from the device are stored in a database and further aggregated to give the patient's fall history in a web application. The web application displays the patient's fall history by showing the patient’s name, age, state, time of fall, and their condition.Ashesi Universit

IoT Networking: Path to Ubiquitous Connectivity

University of Minnesota Ph.D. dissertation. August 2019. Major: Computer Science. Advisor: Tian He. 1 computer file (PDF); xii, 105 pages.Internet of Things (IoT) is upon us with the number of IoT connected devices reach- ing 17.68 billion in the year 2016 and keeps an increasing rate of 17%. The popularity of IoT brings the prosperity and diversity of wireless technologies as one of its founda- tions. Existing wireless technologies, such as WiFi, Bluetooth, and LTE, are evolving and new technologies, such as SigFox and LoRa, are proposed to satisfy various needs under emerging application scenarios. For example, WiFi is evolving to provide higher throughput with the novel 802.11ac technology and the Bluetooth SIG has proposed the Bluetooth Low Energy (BLE) technology to support low-power applications. However, wireless technologies are victims of their own success. The vastly increasing wireless devices compete for the limited wireless spectrum and result in the performance degradation of each device. What makes it worse is that diverse wireless devices are using heterogeneous PHY and MAC layers designs which are not compliant with each other. As a result, sophisticated wireless coordination methods working well for each homogeneous technology are not applicable in the heterogeneous wireless scenario for the failure to communicate among heterogeneous devices. This dissertation aims at fundamentally solving the burden of communication in today’s heterogeneous wireless environment. Specifically, we try to build direct communication among heterogeneous wireless technologies, referred to as the cross-technology communication (CTC). It is counter-intuition and long believed impossible, but we find two opportunities in both the packet level and physical (PHY) layer to make the challenging mission possible. First, wireless devices are commonly able to do energy-sensing of wireless packets in the air. Energy sensing is capable to figure out packet-level information, such as the packet duration and timing. Based on the energy-sensing capability, we design DCTC, a CTC technology that piggybacks cross-technology messages within the timing of transmitted wireless packets. Specifically, we slightly perturb the timing of packets emitted from a wireless device to form detectable energy patterns to establish CTC. Testbed evaluation has shown that we can successfully transmit information at 760bps while keeping the delay of each packet no longer than 0.5ms under any traffic pattern. Second, in the PHY layer, high-end wireless technologies are flexible, i.e., a larger symbol set, in the modulation and demodulation. With careful choices of symbols, those wireless technologies are able to emulate and decode the PHY layer signal of a low-end one. We propose two systems BlueBee and XBee which aim at building direct com- munication between two heterogeneous IoT technologies, Bluetooth and ZigBee, with the idea of signal emulation and cross-decoding respectively. The former achieves signal emulation by carefully choosing the Bluetooth payload bits so that the output signal emulates a legitimate ZigBee packet which can be successfully demodulated by a com- modity ZigBee devices without any changes. The latter proposes a general method to support the bidirectional communication in the PHY-layer CTC by moving the complex- ity to the high-end receiver for the demodulation of signal from a low-end transmitter. Our testbed evaluation has shown that our technologies successfully boost the data rate of the state of the arts by over 10,000x times, which is approaching the ZigBee standard. This result makes CTC possible to play more roles in real-time applications, such as network coordination. In summary, this dissertation provides a new communication paradigm in a heteroge- neous wireless environment, which is to provide direct communication for heterogeneous wireless devices. Such communication is built upon two opportunities: (i) wireless de- vices are capable to sense energy in the air so that specifically designed energy patterns can transmit cross-technology information; (ii) a high-end wireless technology is more flexible and possible to emulate and demodulate the signal from a low-end technology for communication. The technologies developed in the dissertation will be the build- ing blocks for the future designs of efficient channel coordination and ubiquitous data exchange among heterogeneous wireless devices

Design for energy-efficient and reliable fog-assisted healthcare IoT systems

Cardiovascular disease and diabetes are two of the most dangerous diseases as they are the leading causes of death in all ages. Unfortunately, they cannot be completely cured with the current knowledge and existing technologies. However, they can be effectively managed by applying methods of continuous health monitoring. Nonetheless, it is difficult to achieve a high quality of healthcare with the current health monitoring systems which often have several limitations such as non-mobility support, energy inefficiency, and an insufficiency of advanced services. Therefore, this thesis presents a Fog computing approach focusing on four main tracks, and proposes it as a solution to the existing limitations. In the first track, the main goal is to introduce Fog computing and Fog services into remote health monitoring systems in order to enhance the quality of healthcare. In the second track, a Fog approach providing mobility support in a real-time health monitoring IoT system is proposed. The handover mechanism run by Fog-assisted smart gateways helps to maintain the connection between sensor nodes and the gateways with a minimized latency. Results show that the handover latency of the proposed Fog approach is 10%-50% less than other state-of-the-art mobility support approaches. In the third track, the designs of four energy-efficient health monitoring IoT systems are discussed and developed. Each energy-efficient system and its sensor nodes are designed to serve a specific purpose such as glucose monitoring, ECG monitoring, or fall detection; with the exception of the fourth system which is an advanced and combined system for simultaneously monitoring many diseases such as diabetes and cardiovascular disease. Results show that these sensor nodes can continuously work, depending on the application, up to 70-155 hours when using a 1000 mAh lithium battery. The fourth track mentioned above, provides a Fog-assisted remote health monitoring IoT system for diabetic patients with cardiovascular disease. Via several proposed algorithms such as QT interval extraction, activity status categorization, and fall detection algorithms, the system can process data and detect abnormalities in real-time. Results show that the proposed system using Fog services is a promising approach for improving the treatment of diabetic patients with cardiovascular disease

An energy-aware mobile gateway for Bluetooth low energy-powered Internet of Things devices

The term of Internet of Things (IoT) has currently become a novelty in the Internet as an innovation to connect things from all around the world where various sensors are connected using gateways. However, it is not a straightforward task to design such gateways owing to several problems. For instance, there typically exist severe energy consumption constraints due to the limited power source. In most cases, a gateway has to spend an amount of energy for processing the collected data in the network. Additionally, there are myriad of different user interface functions for various services, which in turn raises the question about the reliability and scalability of such gateways. To support the IoT vision, many people have recently used smart mobile devices, e.g., smartphones, tablets, PDA, and laptops, as a gateway for data acquisition in IoT so that these IoT devices can be used in a broader scope. This concept of exploiting our smart devices emerges thanks to their ability to connect things to the cloud via the Internet. In fact, there exist a communication gap between the things implemented with limited power sources to sense the environmental data and the cloud services. Fortunately, this gap can be bridged by adopting smartphones for forwarding the collected data using their wireless connection technologies. One of the critical technologies that can be used to bridge this communication gap while also still maintaining low energy consumption is Bluetooth Low Energy (BLE). As leverage from the original Bluetooth technology, BLE or known as Bluetooth Smart was initially designed as a power-friendly wireless technology aimed for some novel applications in many industries. To save energy, BLE can be set in a sleep mode and wake up only to receive or send possible packet periodically. By the usage of BLE in modern smartphones, a mobile gateway system can be made in a way that data from the sensors can be passed to the cloud while also considering the energy efficiency in the mobile gateway itself. In this thesis, we propose a software architecture of energy-aware mobile gateways for IoT applications. The proposed architecture makes continual and efficient data transmission from a set of predefined devices. Moreover, the gateway architecture implements several scheduling algorithms used to efficiently control the sleep mode operations besides handle the simultaneous connection to several BLE sensors. The presented scheduling algorithms comprise Semaphore, Round Robin, Exhaustive Polling and Fair Exhaustive Polling algorithms. To implement the BLE device priority-based approach, several multi-criteria decision making (MCDM) algorithms are also implemented to prioritize the device based on several criteria, such as device power usage, received signal strength indication and the device state. Examples of such MCDM algorithms that have been implemented in this work are the Analytic Hierarchy Process and the Weighted Sum Model. Furthermore, the algorithms implemented are then evaluated based on two quality of service(QoS) metrics, including the power consumption of the mobile gateway and the throughput defined regarding the number of packets received per second. The evaluation results showed that Fair Exhaustive Polling (FEP) consumes the lowest energy consumption compared to all other scheduling algorithms with only 12,79 mW. On the other hand, Exhaustive Polling with Analytical Hierarchy Process (EPAHP) has the worst energy consumption among the examined algorithms with 49,14 mW. Concerning the throughput, the Exhaustive Polling combined with Weighted Sum Model (EPWSM) has the most prominent data throughput compared to all other algorithms with 101.18 packets/s while Fair Exhaustive Polling (FEP) has the lowest throughput value with 50.98 packets/s. To sum up, the proposed mobile gateway architecture is exceptionally efficient for handling data forwarding from multiple BLE sensors to the cloud services with energy awareness