Browsing by Subject "Internet of Things (IoT)"

Now showing 1 - 6 of 6

Open Access
Classifying daily and sports activities invariantly to the positioning of wearable motion sensor units
(IEEE, 2020) Barshan, Billur; Yurtman, Aras
We propose techniques that achieve invariance to the positioning of wearable motion sensor units on the body for the recognition of daily and sports activities. Using two sequence sets based on the sensory data allows each unit to be placed at any position on a given rigid body part. As the unit is shifted from its ideal position with larger displacements, the activity recognition accuracy of the system that uses these sequence sets degrades slowly, whereas that of the reference system (which is not designed to achieve position invariance) drops very fast. Thus, we observe a tradeoff between the flexibility in sensor unit positioning and the classification accuracy. The reduction in the accuracy is at acceptable levels, considering the convenience and flexibility provided to the user in the placement of the units. We compare the proposed approach with an existing technique to achieve position invariance and combine the former with our earlier methodology to achieve orientation invariance. We evaluate our proposed methodology on a publicly available data set of daily and sports activities acquired by wearable motion sensor units. The proposed representations can be integrated into the preprocessing stage of existing wearable systems without significant effort.
Open Access
Energy harvesting and wireless power transfer enabled wireless networks
(Elsevier, 2020) Duman, Tolga M.; Zhao, N.; Nallanathan, A.; Chen, Y.; Pan, M.
Development of wireless communication networks, connected devices, and improvement of Internet of Things (IoT) will deeply impact in every aspect of human life. In future mobile systems, a tremendous number of low-power wireless devices will exist within the densely deployed heterogeneous networks. One key challenge from the growing demand in wireless applications is a sufficient and flexible energy supply. Hence, a natural spin from the traditional and limited energy sources to alternative energy sources is a natural step to supply the exponential growth of energy demand of the mankind. Recently, energy harvesting (EH) has emerged as an important method to provide a power supply for green self-sufficient wireless nodes, in which the energy captured from intentional or ambient sources can be collected to replenish the batteries. Besides, EH has been investigated as a promising technology to overcome the energy scarcity problem in energy constrained wireless communication systems, especially for wireless networks with fixed energy supplies. Compared with conventional EH sources such as solar, wind, vibration, thermoelectric effects or other physical phenomena, which rely on external energy sources that are not components of communication networks, a new operation of EH which collects energy from ambient radio-frequency (RF) signals has been proposed. As RF signals are commonly used as a vehicle for transmitting information in wireless networks, simultaneous wireless information and power transfer (SWIPT) has become an emerging technique attracting great attention from both academia and industry. Towards this end, this special issue includes a collection of 24 papers, and we aim to disseminate the latest research and innovations on energy harvesting and wireless power transfer enabled wireless networks.
Open Access
Estimation theoretic secure communication via encoder randomization
(IEEE, 2019-12-01) Göken, Çağrı; Gezici, Sinan
Estimation theoretic secure transmission of a scalar random parameter is investigated in the presence of an eavesdropper. The aim is to minimize the estimation error at the receiver under a secrecy constraint at the eavesdropper; or, alternatively, to maximize the estimation error at the eavesdropper for a given estimation accuracy limit at the receiver. In the considered setting, the encoder at the transmitter is allowed to use a randomized mapping between two one-to-one and continuous functions and the eavesdropper is fully aware of the encoding strategy at the transmitter. For small numbers of observations, both the eavesdropper and the receiver are modeled to employ linear minimum mean-squared error (LMMSE) estimators, and for large numbers of observations, the expectation of the conditional Cramér-Rao bound (ECRB) metric is employed for both the receiver and the eavesdropper. Optimization problems are formulated and various theoretical results are provided in order to obtain the optimal solutions and to analyze the effects of encoder randomization. In addition, numerical examples are presented to corroborate the theoretical results. It is observed that stochastic encoding can bring significant performance gains for estimation theoretic secrecy problems.
Open Access
Load balancing enhancements to the routing protocol for low power and lossy networks in the internet of things
(2018-11) Noor, Hira
The internet today is shifting from the Internet of people to the Internet of Things (IoT). Particularly, in IoTs, wireless sensors connect edge devices to the Internet via a gateway that provides connectivity between wireless sensor networks (WSNs) and the Internet. IoT includes a variety of heterogeneous network applications ranging from smart grid automated metering infrastructures (AMIs), industrial and environmental monitoring networks to building automation. In WSNs, congestion causes a plenty of impairments such as increased packet losses, lower throughput, and energy wastage thus decreasing the lifetime and performance of wireless sensor applications. IPv6 over Low Power Wireless Personal Area Networks (6LoWPAN) is envisioned to be used in the majority of IoT applications. Recently, the Internet Engineering Task Force (IETF) Routing over Low power and Lossy Networks (ROLL) working group has proposed a Routing Protocol for Low power and Lossy networks called RPL. RPL is often studied in a multipoint-to-point sink node (MP2P) scenarios. We investigate the load balancing and congestion problem of RPL. RPL su ers from congestion and unbalanced load distribution due to the use of a single path for multipoint-to-point traffic. In particular, we propose queue utilization-based multipath RPL (QU-MRPL). In QU-MRPL, multiple parents are selected based on their queue size information. We demonstrate that QU-MRPL achieves load balance in the network and thus increases the packet delivery ratio.
Open Access
Position invariance for wearables: interchangeability and single-unit usage via machine learning
(IEEE, 2021) Yurtman, Aras; Barshan, Billur; Redif, S.
We propose a new methodology to attain invariance to the positioning of body-worn motion-sensor units for recognizing everyday and sports activities. We first consider random interchangeability of the sensor units so that the user does not need to distinguish between them before wearing. To this end, we propose to use the compact singular value decomposition (SVD) that significantly reduces the accuracy degradation caused by random interchanging of the units. Secondly, we employ three variants of a generalized classifier that requires wearing only a single sensor unit on any one of the body parts to classify the activities. We combine both approaches with our previously developed methods to achieve invariance to both position and orientation, which ultimately allows the user significant flexibility in sensor-unit placement (position and orientation). We assess the performance of our proposed approach on a publicly available activity dataset recorded by body-worn motion-sensor units. Experimental results suggest that there is a tolerable reduction in accuracy, which is justified by the significant flexibility and convenience offered to users when placing the units.
Open Access
Safety tracking system for bathroom shower environment
(IEEE, 2024-05-12) Ölmez, Eren; Özsoy, Mehmet Oktay; Jabiyev, Ramil; Ansen, Beren; Akturk, Umut Eren; Oral, Ege Bora; Soygür, Can; Barshan, Billur; Kutay, Mehmet Alper; Afacan, Yasemin
This study is aimed at recognizing fall incidents that occur in the bathroom shower area. Bathroom falls are one of the primary reasons for injuries (which can be fatal), especially for the elderly. For that reason, a system that can detect bathroom falls and trigger necessary emergency scenarios is implemented. To that end, a system comprising radar sensors and IMUs is implemented. The information regarding the door and the shower head is used in a supportive way for fall detection. If a fall is detected, fall occurrence warning is sent to the necessary destinations through IoT.