IoT-TD: IoT Dataset for Multiple Model BLE-based Indoor Localization/Tracking

Salimibeni, Mohammad; Hajiakhondi-Meybodi, Zohreh; Malekzadeh, Parvin; Atashi, Mohammadamin; Plataniotis, Konstantinos N.; Mohammadi, Arash

doi:10.23919/eusipco47968.2020.9287547

Cited by 12 publications

(3 citation statements)

References 22 publications

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“…Also, path loss may influence by terrain contours, environment (urban or rural, vegetation, and foliage), propagation medium (dry or moist air), the distance between the transmitter and the receiver, and the height and location of antennas. The accuracy of the calculation of the path loss would affect the accuracy of our positioning 61 . This stress‐free floor plan and its intersections of the mesh grid provide sample space.…”

Section: Proposed Methodsmentioning

confidence: 99%

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THIP: A trajectory history‐based indoor positioning algorithm using stress‐free floor plan for patient monitoring

Jalali

Kheirabadi

2023

Int J Communication

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Summary The Internet of Things (IoT) is a novel paradigm that consists of a wide network of machines and intelligent devices with the capability of communication and interaction with each other. One of the significant issues for the IoT is its healthcare applications. The positioning systems based on their environment can be classified into two main categories: Indoor and outdoor. Recently, IoT indoor positioning attracts too much attention among researchers for patient monitoring. Hence, in this paper, a stress‐free floor plan indoor positioning algorithm for patient monitoring is proposed, called THIP. The history of the patient's movement is stored in a trajectory history, and this information is employed to estimate the patient's more accurate position. The proposed THIP algorithm is simulated in MATLAB software. Several experiments are conducted to evaluate the performance of the proposed algorithm. Simulation results show that the proposed THIP algorithm raises patient positioning accuracy and declines the distance error cumulative compared to LiFS by about 4.68% and 60.6 m, respectively. Moreover, it can identify the floor level of the moving user.

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Section: Proposed Methodsmentioning

confidence: 99%

“…The accuracy of the calculation of the path loss would affect the accuracy of our positioning. 61 This stress-free floor plan and its intersections of the mesh grid provide sample space. We consider each sample space as 1 m * 1 m square, which helps us achieve high positioning accuracy.…”

Section: Path Lossmentioning

confidence: 99%

THIP: A trajectory history‐based indoor positioning algorithm using stress‐free floor plan for patient monitoring

Jalali

Kheirabadi

2023

Int J Communication

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“…There are several public Wi-Fi datasets for Wi-Fi-based positioning systems, [13][14][15][16][17][18][19], which are collected in a variety of scenarios, including universities, office buildings, shopping malls, and industrial factory-like space. There are also hybrid datasets, namely, with Wi-Fi and Bluetooth Low Energy (BLE) data [20], with Wi-Fi, BLE, and Zigbee [21], with Wi-Fi, BLE, and magnetometer data [22], with BLE and IMU data [23], or even with Wi-Fi, BLE, cellular signal and multi-sensor data (magnetometer, accelerometer, gyroscope, barometer, and ambient light sensor) [24]. The International Conference on Indoor Positioning and Indoor Navigation (IPIN) provides their competitions' datasets, containing multi-sensor data along with ground truth [25][26][27][28][29][30][31][32][33][34], which are available at https://ipin-conference.org/resources.html (accessed on 7 July 2023).…”

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confidence: 99%

Industrial Environment Multi-Sensor Dataset for Vehicle Indoor Tracking with Wi-Fi, Inertial and Odometry Data

Silva,

Pendão,

Torres-Sospedra

et al. 2023

Data

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This paper describes a dataset collected in an industrial setting using a mobile unit resembling an industrial vehicle equipped with several sensors. Wi-Fi interfaces collect signals from available Access Points (APs), while motion sensors collect data regarding the mobile unit’s movement (orientation and displacement). The distinctive features of this dataset include synchronous data collection from multiple sensors, such as Wi-Fi data acquired from multiple interfaces (including a radio map), orientation provided by two low-cost Inertial Measurement Unit (IMU) sensors, and displacement (travelled distance) measured by an absolute encoder attached to the mobile unit’s wheel. Accurate ground-truth information was determined using a computer vision approach that recorded timestamps as the mobile unit passed through reference locations. We assessed the quality of the proposed dataset by applying baseline methods for dead reckoning and Wi-Fi fingerprinting. The average positioning error for simple dead reckoning, without using any other absolute positioning technique, is 8.25 m and 11.66 m for IMU1 and IMU2, respectively. The average positioning error for simple Wi-Fi fingerprinting is 2.19 m when combining the RSSI information from five Wi-Fi interfaces. This dataset contributes to the fields of Industry 4.0 and mobile sensing, providing researchers with a resource to develop, test, and evaluate indoor tracking solutions for industrial vehicles.

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Security Services for Wireless 5G Internet of Things (IoT) Systems

Malik,

Parihar,

Bhushan

et al. 2023

Springer Tracts in Electrical and Electronics Engineering

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The Internet of Things (IoT) is an emerging field that has evolved in recent past years and tends to have a major effect on our lives in the coming future. The development of communication techniques is very rapid and tends to achieve many innovative results. With the invention of 5th Generation mobile networks, i.e., 5G, it is becoming an exciting and challenging topic of interest in the field of wireless communication. 5G networks have the ability to connect millions or billions of nodes without affecting the quality of throughput and latency. The 5G technology can develop a truly digital society in which every device may be connected through the Internet. IoT is an emerging technology in which everything can be connected and communicated via the Internet, the term everything may include computing devices, humans, software, platforms, and solutions. The development of this technology leads to the advent of a number of solutions that are helpful for humankind, for example, smart retailing creation of smart cities, smart farming, intelligent transport systems, smart eco-systems, etc. While IoT is a revolutionary technology in the progression of the Internet, it still has some significant challenges for implementation like ensuring security, performance issues, quality of support and saving of energy, etc. Furthermore, the paper elaborates on the motivation of combining two technology together named IoT and 5G for better communication. Additionally, the paper illustrates the basic architecture of IoT enabling 5G and discussed various solutions to provide communication. Moreover, the paper also discussed the various challenges and research gaps of 5G-IoT technology.

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IoT-TD: IoT Dataset for Multiple Model BLE-based Indoor Localization/Tracking

Cited by 12 publications

References 22 publications

THIP: A trajectory history‐based indoor positioning algorithm using stress‐free floor plan for patient monitoring

THIP: A trajectory history‐based indoor positioning algorithm using stress‐free floor plan for patient monitoring

Industrial Environment Multi-Sensor Dataset for Vehicle Indoor Tracking with Wi-Fi, Inertial and Odometry Data

Security Services for Wireless 5G Internet of Things (IoT) Systems

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