NSF CNS Award #1816387 NETS:SMALL: Functional Fabrics for the Internet of Things

Personnel:

PI: Kapil R. Dandekar
Co-PIs: Genevieve Dion, William Mongan, Steven Weber

Post Doctoral Researchers:

Chelsea Amanatides
Vasil Pano

Graduate Students:

Abhinanda Dutta
Md Shakir Hossain
Marko Jacovic
Hariharan Narayanan
Md Abu Saleh Tajin
Xaime Rivas Rey

Undergraduate Students

Rei Ballabani
Claudia Offut
Lauren Douglas
Kevin Hoffman
Abe Jeyaprathap
Nate Judd
Martin Kraus
Neil Kanakia
Sahithi Pisupati
Daniel Rodriguez
Samuel Toseafa
Adeeb Abbas
Stephen Hansen
Daniel Schwartz
Jesse Stover
Celine Kho
Kristopher Lopez
Daniel Rodriguez
Aleksandar Dunjic
Aleksandar Aleksandrov
Mathilda Nguyen
Noah McCarthy
Ian Utz
Mathhew Wallace

Goals

Functional fabrics are textiles designed to perform a wide variety of functions with applications ranging from medicine and sports to realizing the “soft” side (e.g., clothing, drapes, upholstery) of the Internet of Things (IoT). Coupled with pervasive access to smart phones and wireless Internet, they are enabling exciting new application domains, notably in smart homes and wearable health systems. Whereas the majority of these devices today are similar in form to a wrist watch, the next generation of wearables for the Internet of Things are likely to be fully integrated into textile turning the fabric into garment and textile devices.

The functional fabrics that we envision will be ubiquitous and unobtrusive. If designed properly, the user should not even realize that they are surrounded by this technology. The design of functional fabrics will be fully flexible, scalable, and customizable to individuals. The applications they enable will vary widely between what will one day be seen as: mundane (e.g., smart drapes with sensors that measure and regulate temperature within a room), convenient (e.g., smart laundry that will help prevent bright colored clothing from being washed with whites), personal / professional productivity (e.g., convergence of functional fabrics with voice and data transceivers for social / work applications), as well as life-changing/saving (e.g., biomedical functional fabrics with textile based sensors). The use of passive radio frequency identification (RFID), in particular, is an enabling technology for high density Internet of Things deployments since each functional fabric device would not require a battery or cumbersome transceiver electronics.

Intellectual merit

Major Goal #1: Cognitive Passive RFID - We will i.) design a testbed for functional fabric, passive RFID IoT systems using a network of software defined radio (SDR) based interrogators capable of serving high densities of functional fabrics representative of IoT deployments, ii.) develop localization and processing algorithms using collaborative interrogator beamforming techniques, and iii.) consider security and privacy issues in the data collected by our RFID IoT system.

Major Goal #2: Interrogator Message Concentration Protocol - We consider the challenge in delivering messages from high density IoT device deployments gathered by the RFID interrogators (received in turn from the RFID tags) to the Internet or cloud.

Major Goal #3: Architectures and Protocols for Wearable IoT Sensor Networks - We will develop architectures and protocols to utilize passive, high-density, heterogeneous sensor systems integrated in functional fabrics to serve, access and be accessed by an IoT vertical.

Broader impacts

Broader impacts of the proposed project included the mentoring of graduate and undergraduate students. This mentoring includes use of the new Drexel Vertically Integrated Projects (VIP) program involving undergraduate students in research. We are developing augmented reality visualization tools for IoT applications. Finally, we also consider technology commercialization in coordination with the Pennsylvania Fabric Discovery Center as part of the Advanced Functional Fabrics of America (AFFOA) institute.

Activities

Some current activities from this project include:

• Pattern Reconfigurable UHF RFID Reader Antenna Array - The growing research interest in passive RFID (Radio Frequency Identification)-based devices and sensors in a diverse group of applications calls for flexibility in reader antenna performance. We developed a low-cost, easy-to-fabricate, and pattern reconfigurable UHF (Ultra High Frequency) RFID reader antenna in the RFID ISM band (902-928 MHz in the US). The antenna offers a 54 MHz bandwidth (890 - 944 MHz) and 8.9 dBi maximum gain. The reconfigurable antenna can radiate four electronically switchable radiation beams in the azimuth plane. The antenna is LHCP (Left Hand Circularly Polarized) with axial ratio (AR) in the ranging from 0.45 dB to 7 dB in the RFID ISM band. Simulation and measurements are presented, and they are in good agreement. The proposed reader array performance is compared against a commercially available reader antenna. The pattern reconfigurable UHF RFID reader antenna not only increases the coverage area for conventional RFID applications but also opens the door to on-body RFID sensor implementation and indoor localization applications.

• UHF RFID Channel Emulation Testbed for Wireless IoT Systems - We developed an UHF RFID channel emulation testbed that is capable of simultaneously emulating unique wireless channels. The proposed system can potentially be an invaluable tool in the design and validation of RFID-based IoT sensors and systems. Emulation of ray-tracing-based wireless channels enables the evaluation of inherently difficult and complex RF scenarios, particularly in situations when in-person experimentation is not feasible or desirable ( e.g., during a pandemic or in a critical care facility). Furthermore, the emulation testbed is able to generate a large amount of sensor data in a limited time period. Machine learning techniques used in wireless IoT can be greatly enhanced by a large amount of data extracted from the emulation of dynamic and challenging environments. The proposed multi-channel emulation testbed is therefore a valuable solution for experimentation on real hardware and a convenient tool for pre-clinical-trial system validation.

• Passive UHF RFID-based Knitted Wearable Compression Sensor - One of the major challenges faced by passive on-body IoT sensors is the absorption of radiated power by tissues in the human body. We present a batteryless, wearable knitted UHF RFID compression sensor (Bellypatch) antenna and show its applicability as an on-body respiratory monitor for medical IoT. The antenna radiation efficiency is satisfactory in both free-space and on-body operations. We extract RF sheet resistance values of three knitted silver-coated nylon fabric candidates at 913 MHz. The best type of fabric is selected based on the extracted RF sheet resistance. Simulated and measured performance of the antenna confirm the suitability for on-body medical IoT applications.

• Solution-Processed Ti3C2Tx MXene Antennas for Radio-Frequency Communication - Highly integrated, flexible, and ultrathin wireless communication components are in significant demand due to the explosive growth of portable and wearable electronic devices in the IoT era, but only conventional metals meet the requirements for emerging RF devices so far. Here, it is reported on Ti3C2Tx MXene microstrip transmission lines with low-energy attenuation and patch antennas with high-power radiation at frequencies from 5.6 to 16.4 GHz. The radiation efficiency of a 5.5 µm thick MXene patch antenna manufactured by spray-coating from aqueous solution reaches 99% at 16.4 GHz, which is about the same as that of a standard 35 µm thick copper patch antenna at about 15% of its thickness and 7% of the copper weight. MXene outperforms all other materials evaluated for patch antennas to date. The versatility of MXene antennas in wide frequency ranges coupled with the flexibility, scalability, and ease of solution processing makes MXene promising for integrated RF components in various flexible electronic devices, and an exciting new enabling technology for future IoT devices.

• Channel Emulation for the Characterization of Wearable RFID Systems - Wearable sensors with RFID tags are considered to be an integral part of the upcoming revolution in the IoT sector. As with many deployed IoT sensor systems, dynamic environment conditions present challenges in reliably measuring system performance; this difficulty is enhanced due to proprietary details about the sensors, such as an RFID chip embedded within a novel knitted antenna acting as a passive sensor. A repeatable and scalable platform is necessary to evaluate the performance of the entire system in the pre-deployment stage in order to compare the predicted effects of varying components, design, and integration of sensors in an integrated IoT device. This paper demonstrates the development of an RFID channel emulation testbed in the United States ISM band. The testbed includes a commercial RFID interrogator, a custombuilt circuit board housing a commercial passive RFID chip, and a dynamic spectrum environment emulator (DYSE) for wireless channel emulation. A single link scenario was considered where the DYSE emulates the antenna gain fluctuation due to the sensing of breathing with a fabric-based RFID. Two regular and one irregular breathing scenarios were emulated, and breathing rate or anomaly was detected from post-processed RSSI (Received Signal Strength Indicator) data received by the RFID interrogator.

• Real-time Online Learning for Pattern Reconfigurable Antenna State Selection - Pattern reconfigurable antennas (PRAs) can dynamically change their radiation pattern and provide diversity and directional gain. These properties allow them to adapt to channel variations by steering directional beams toward desired transmissions and away from interference sources, thus enhancing the overall performance of a wireless communication system. To fully exploit the benefits of a PRA, the key challenge is being able to optimally select the antenna state in real time. Current literature on this topic, to the best of our knowledge, focuses on the design of algorithms to optimally select the best antenna mode with evaluation performed in simulation or postprocessing. In this study, we have not only designed a real-time online antenna state selection framework for SISO wireless links but we have also implemented it in an experimental software defined radio testbed. We benchmarked the multi-armed bandit algorithm against other antenna state selection algorithms and show how it can improve system performance by mitigating the effects of interference taking advantage of the directionality PRAs provide. We also show that when the optimal state changes over time the bandit approach does not work very well. For such a scenario, we show how the Adaptive Pursuit algorithm works well and can be a great solution. We also discuss what changes could be done to the bandit algorithm to work better in this case. In planned research, this antenna will be integrated with our reconfigurable IoT reader antenna.

• Extraction of Knitted RFID Antenna Design Parameter from Transmission Line Measurements - The seamless integration of knitted antennas into electronic devices requires accurate knowledge of the electrical properties of the conductive fabrics at high frequencies. We demonstrted a new method of extracting sheet resistance of knitted conductive fabric from S-parameter measurements of two-port transmission lines. The extracted sheet resistance parameter is then used to simulate knitted antennas for IoT applications.

Publications

Tajin, Md Abu and Jacovic, Marko and Mongan, William and Dandekar, Kapil R. (2021). Channel Emulation for the Characterization of Wearable RFID Systems. 2021 IEEE 21st Annual Wireless and Microwave Technology Conference (WAMICON). 1 to 5. Published. https://doi.org/10.1109/WAMICON47156.2021.9443623.

Han, Meikang and Liu, Yuqiao and Rakhmanov, Roman and Israel, Christopher and Tajin, Md Abu and Friedman, Gary and Volman, Vladimir and Hoorfar, Ahmad and Dandekar, Kapil R. and Gogotsi, Yury (2021). Solution‐Processed Ti 3 C 2 T x MXene Antennas for Radio‐Frequency Communication. 33. (1). Advanced Materials, 33. 2003225. Published. 0935-9648. https://doi.org/10.1002/adma.202003225.

Tajin, Md Abu and Jacovic, Marko and Dion, Genevieve and Mongan, William M. and Dandekar, Kapil R. (2021). UHF RFID Channel Emulation Testbed for Wireless IoT Systems. IEEE Access. 1 to 1. Published. 2169-3536. https://doi.org/10.1109/ACCESS.2021.3077845.

Tajin, Md Abu and Amanatides, Chelsea E. and Dion, Genevieve and Dandekar, Kapil R. (2021). Passive UHF RFID-based Knitted Wearable Compression Sensor. IEEE Internet of Things Journal. 1 to 1. Published. 2372-2541. https://doi.org/10.1109/JIOT.2021.3068198.

Tajin, Md Abu and Jacovic, Marko and Mongan, William and Dandekar, Kapil R. (2020). Channel Emulation for the Characterization of Wearable RFID Systems. IEEE 21st Annual Wireless and Microwave Technology Conference (WAMICON) (WAMICON 2020). Published.

Tajin, Md Abu and Dandekar, Kapil R. (2020). Pattern Reconfigurable UHF RFID Reader Antenna Array. 8. IEEE Access, 8. 187365 to 187372. Published. 2169-3536. https://doi.org/10.1109/ACCESS.2020.3031296.

Rey, Xaime Rivas and Mainland, Geoffrey and Dandekar, Kapil (2020). Real-time Online Learning for Pattern Reconfigurable Antenna State Selection. 2020 7th NAFOSTED Conference on Information and Computer Science (NICS). 13 to 18. Published. https://doi.org/10.1109/NICS51282.2020.9335872.

Tajin, Md Abu and Levitt, Ariana S. and Liu, Yuqiao and Amanatides, Chelsea E. and Schauer, Caroline L. and Dion, Genevieve and Dandekar, Kapil R. (2020). Extraction of Knitted RFID Antenna Design Parameter from Transmission Line Measurements. 2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting. 1551 to 1552. Published. https://doi.org/10.1109/IEEECONF35879.2020.9329989.

Tajin, Md Abu and Mongan, William M. and Dandekar, Kapil R. (2020). Passive RFID-based Diaper Moisture Sensor. IEEE Sensors Journal. 1 to 1. Published. 1530-437X. 10.1109/JSEN.2020.3021395.

Tajin, Md Abu and Bshara, Oday and Liu, Yuqiao and Levitt, Ariana and Dion, Genevieve and Dandekar, Kapil R. (2020). Efficiency measurement of the flexible on-body antenna at varying levels of stretch in a reverberation chamber. 14. (3). IET Microwaves, Antennas & Propagation, 14. 154 to 158. Published. 1751-8725. 10.1049/iet-map.2019.0503.

Tajin, Md Abu and Levitt, Ariana S. and Liu, Yuqiao and Amanatides, Chelsea E. and Schauer, Caroline L. and Dion, Genevieve and Dandekar, Kapil R. (2020). On the Effect of Sweat on Sheet Resistance of Knitted Conductive Yarns in Wearable Antenna Design. 19. (4). IEEE Antennas and Wireless Propagation Letters, 19. 542 to 546. Published. 1536-1225. 10.1109/LAWP.2020.2971189.

Jacovic, Marko and Juretus, Kyle and Kandasamy, Nagarajan and Savidis, Ioannis and Dandekar, Kapil R. (2020). Physical Layer Encryption for Wireless OFDM Communication Systems. Journal of Hardware and Systems Security. Published. 2509-3428. 10.1007/s41635-020-00097-8.

O’Neill, P. and Mongan, W. M. and Ross, R. and Acharya, S. and Fontecchio, A. and Dandekar, K. R. (2019). An Adaptive Search Algorithm for Detecting Respiratory Artifacts Using a Wireless Passive Wearable Device. 2019 IEEE Signal Processing in Medicine and Biology Symposium (SPMB). 1 to 6. Published. https://doi.org/10.1109/SPMB47826.2019.9037861.

Bshara, Oday and Liu, Yuqiao and Dandekar, Kapil R. (2019). Radar Cross Section Measurement Comparison of UAVs at C-band and V-band. 2019 IEEE 20th Wireless and Microwave Technology Conference (WAMICON). 1 to 6. Published. https://doi.org/10.1109/WAMICON.2019.8765431.

Jacovic, Marko and Kraus, Martin and Mainland, Geoffrey and Dandekar, Kapil R. (2019). Evaluation of Physical Layer Secret Key Generation for IoT Devices. 2019 IEEE 20th Wireless and Microwave Technology Conference (WAMICON). 1 to 6. Published. 10.1109/WAMICON.2019.8765465.

Narayanan, Hariharan and Weber, Steven (2019). Sum throughput on a random access erasure collision channel. 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton). 687 to 694. Published. 10.1109/ALLERTON.2019.8919928.

Acharya, Sayandeep and Mongan, William M. and Rasheed, Ilhaan and Liu, Yuqiao and Anday, Endla and Dion, Genevieve and Fontecchio, Adam and Kurzweg, Timothy and Dandekar, Kapil R. (2019). Ensemble Learning Approach via Kalman Filtering for a Passive Wearable Respiratory Monitor. 23. (3). IEEE Journal of Biomedical and Health Informatics, 23. 1022 to 1031. Published. 2168-2194. 10.1109/JBHI.2018.2857924.

O’Neill, Patrick and Mongan, William and Ross, Robert and Acharya, Sayandeep and Fontecchio, Adam and Dandekar, Kapil R. (2019). An Adaptive Search Algorithm for Detecting Respiratory Artifacts Using a Wireless Passive Wearable Device. 2019 IEEE Signal Processing in Medicine and Biology Symposium. Published.

Gentry, Austin and Mongan, William and Lee, Brent and Montgomery, Owen and Dandekar, Kapil (2019). Activity Segmentation Using Wearable Sensors for DVT/PE Risk Detection. 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC). 477 to 483. Published. 10.1109/COMPSAC.2019.10252.

Chacko, James and Juretus, Kyle and Jacovic, Marko and Sahin, Cem and Kandasamy, Nagarajan and Savidis, Ioannis and Dandekar, Kapil R. (2019). Securing Wireless Communication via Hardware-Based Packet Obfuscation. Journal of Hardware and Systems Security. Published. 2509-3428. 10.1007/s41635-019-00070-0.

Abhinanda Dutta and Steven Weber (2021). Throughput bound minimization for random access channel assignment. Proceedings of the 19th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt). Accepted. Yes.