scholarly journals Monitoring of Cow Location in a Barn by an Open-Source, Low-Cost, Low-Energy Bluetooth Tag System

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3841
Author(s):  
Victor Bloch ◽  
Matti Pastell
Keyword(s):  
Open Space ◽  
Indoor Localization ◽  
Low Cost ◽  
Farm Management ◽  
Propagation Model ◽  
Low Energy ◽  
Long Distance ◽  
Acceleration Measurement ◽  
Localization Accuracy ◽  
Cost System

Indoor localization of dairy cows is important for cow behavior recognition and effective farm management. In this paper, we propose a low-cost system for low-accuracy cow localization based on the reception of signals sent by an acceleration measurement system using the Bluetooth Low Energy protocol. The system consists of low-cost tags and receiving stations. The tag specifications and the localization accuracy of the system were studied experimentally. The received signal strength propagation model and dependence on the tag orientation was studied in an open-space and a barn environment. Two experiments for the evaluation of localization accuracy were conducted with 35 and 19 cows for two days. The localization reference was achieved from feeding stations, a milking robot and videos of cows decoded manually. The localization accuracy (mean ± standard deviation) was 3.27 ± 2.11 m for the entire barn (10 × 40 m2) and 1.9 ± 0.67 m for a smaller area (4 × 5 m2). The system can be used for recognizing long-distance walking, crowded areas in the barn, e.g., queues to milking robots, and cow’s preferable locations. The estimated system cost was 500 + 20 × (cow number) € for one barn. The system has open-access software and detailed instructions for its installation and usage.

scholarly journals Graph-based Semi-supervised Learning for Indoor Localization Using Crowdsourced Data

2017 ◽  
Author(s):  
Liye Zhang ◽  
Shahrokh Valaee ◽  
Yu Bin Xu ◽  
Lin Ma ◽  
Farhang Vedadi
Keyword(s):  
Supervised Learning ◽  
Indoor Localization ◽  
Signal Propagation ◽  
Propagation Model ◽  
Localization Accuracy ◽  
Crowdsourced Data ◽  
Negative Effect ◽  
Rapid Deployment ◽  
Radio Map ◽  
Localization Systems

Indoor positioning based on the received signal strength (RSS) of the WiFi signal has become the most popular solution for indoor localization. In order to realize the rapid deployment of indoor localization systems, solutions based on crowdsourcing have been proposed. However, compared to conventional methods, crowdsourced RSS values are more erroneous and can result in large localization errors. To mitigate the negative effect of the erroneous measurements, a graph-based semi-supervised learning (G-SSL) method is used to exploit the correlation between the RSS values at nearby locations to estimate an optimal RSS value at each location. Before using the G-SSL method, the Linear Regression (LR) algorithm is proposed to solve the device diversity problem in crowdsourcing system. Since the spatial distribution of the APs is sparse, the Compressed Sensing (CS) method is applied to precisely estimate the location of the APs. Based on the location of the APs and a simple signal propagation model, the RSS difference between different locations is calculated and used as an additional constraint to improve the performance of G-SSL. Furthermore, to exploit the sparsity of the weights used in the G-SSL, we use the CS method to reconstruct these weights more accurately and make a further improvement on the performance of the G-SSL. Experimental results show improved results in terms of the smoothness of the radio map and the localization accuracy.

scholarly journals Evaluating the Implications of Varying Bluetooth Low Energy (BLE) Transmission Power Levels on Wireless Indoor Localization Accuracy and Precision

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3282 ◽  
Author(s):  
Umair Mujtaba Qureshi ◽  
Zuneera Umair ◽  
Gerhard Petrus Hancke
Keyword(s):  
Indoor Localization ◽  
Low Energy ◽  
Transmission Power ◽  
Pass Filter ◽  
Bluetooth Low Energy ◽  
Localization Accuracy ◽  
Localization Model ◽  
Localization Precision ◽  
The Impact ◽  
Wireless Indoor Localization

Bluetooth Low Energy (BLE) based Wireless Indoor Localization System (WILS) with high localization accuracy and high localization precision is a key requirement in enabling the Internet of Things (IoT) in today’s applications. In this paper, we investigated the effect of BLE signal variations on indoor localization caused by the change in BLE transmission power levels. This issue is not often discussed as most of the works on localization algorithms use the highest power levels but has important practical implications for energy efficiency, e.g., if a designer would like to trade-off localization performance and node lifetime. To analyze the impact, we used the established trilateration based localization model with two methods i.e., Centroid Approximation (CA) and Minimum Mean Square Error (MMSE). We observed that trilateration based localization with MMSE method outperforms the CA method. We further investigated the use of two filters i.e., Low Pass Filter (LPF) and Kalman Filter (KF) and evaluated their effects in terms of mitigating the random variations from BLE signal. In comparison to non-filter based approach, we observed a great improvement in localization accuracy and localization precision with a filter-based approach. Furthermore, in comparison to LPF based trilateration localization with CA, the performance of a KF based trilateration localization with MMSE is far better. An average of 1 m improvement in localization accuracy and approximately 50% improvement in localization precision is observed by using KF in trilateration based localization model with the MMSE method. In conclusion, with KF in trilateration based localization model with MMSE method effectively eliminates random variations in BLE RSS with multiple transmission power levels and thus results in a BLE based WILS with high accuracy and high precision.

scholarly journals IoT Enabled BLE and LoRa based Indoor Localization without GPS

2021 ◽  
Vol 12 (4) ◽  
pp. 1637-1651
Author(s):  
P Kanakaraja, Et. al.
Keyword(s):  
Open Space ◽  
Indoor Localization ◽  
Low Energy ◽  
Gps Tracking ◽  
Location Tracking ◽  
Gps Receiver ◽  
Indoor Location ◽  
The World ◽  
Exact Position ◽  
The Common

The common problem that people face these days to find out the Indoor location of a particular Object or a Person exactly. GPS-based location tracking is one of the very important services nowadays. To use GPS tracking to find a path to our destination and also track the position of our goods using GPS Tracking. It is also possible to track the exact location in absence of GPS with the help of proposed implementation. In some cases like indoor location, the GPS tracker cannot locate exact position of a person or an object. GPS Tracker generally requires an open space with no roof on it. Bluetooth Low Energy (BLE) iBeacons that have to understand basically where this technology can be used or where it is useful. Basically, it is for an especially indoor location tracking of something movable or mobile without the use of a GPS Receiver. This proposed article is going to discuss the idea of making an Indoor location tracker using BLE and LoRa Technology along with IoT Dashboard through “The Things Network” (TTN) to know the position of the object or a person anywhere in the world

scholarly journals An Automated Indoor Localization System for Online Bluetooth Signal Strength Modeling Using Visual-Inertial SLAM

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2857
Author(s):  
Simon Tomažič ◽  
Igor Škrjanc
Keyword(s):  
Data Acquisition ◽  
Indoor Localization ◽  
Low Cost ◽  
Path Loss ◽  
Signal Strength ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Localization System ◽  
Good Trade ◽  
Strength Modeling

Indoor localization is becoming increasingly important but is not yet widespread because installing the necessary infrastructure is often time-consuming and labor-intensive, which drives up the price. This paper presents an automated indoor localization system that combines all the necessary components to realize low-cost Bluetooth localization with the least data acquisition and network configuration overhead. The proposed system incorporates a sophisticated visual-inertial localization algorithm for a fully automated collection of Bluetooth signal strength data. A suitable collection of measurements can be quickly and easily performed, clearly defining which part of the space is not yet well covered by measurements. The obtained measurements, which can also be collected via the crowdsourcing approach, are used within a constrained nonlinear optimization algorithm. The latter is implemented on a smartphone and allows the online determination of the beacons’ locations and the construction of path loss models, which are validated in real-time using the particle swarm localization algorithm. The proposed system represents an advanced innovation as the application user can quickly find out when there are enough data collected for the expected radiolocation accuracy. In this way, radiolocation becomes much less time-consuming and labor-intensive as the configuration time is reduced by more than half. The experiment results show that the proposed system achieves a good trade-off in terms of network setup complexity and localization accuracy. The developed system for automated data acquisition and online modeling on a smartphone has proved to be very useful, as it can significantly simplify and speed up the installation of the Bluetooth network, especially in wide-area facilities.

Low-Cost System Handles Patient Phone Calls

2007 ◽  
Vol 40 (11) ◽  
pp. 53
Author(s):  
BRUCE K. DIXON
Keyword(s):  
Low Cost ◽  
Cost System ◽  
Phone Calls

Intelligent, low-cost system for fume control during laser material processing

2005 ◽  
Author(s):  
Ramin Sattari ◽  
Stephan Barcikowski ◽  
Thomas Püster ◽  
Andreas Ostendorf ◽  
Heinz Haferkamp
Keyword(s):  
Material Processing ◽  
Low Cost ◽  
Laser Material Processing ◽  
Laser Material ◽  
Cost System

scholarly journals A Long-Distance Communication Architecture for Medical Devices Based on LoRaWAN Protocol

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 940
Author(s):  
Nicoleta Cristina Gaitan
Keyword(s):  
Energy Consumption ◽  
Long Range ◽  
Medical Devices ◽  
Low Energy ◽  
Area Network ◽  
Wide Area Network ◽  
Long Distance ◽  
Communication Architecture ◽  
Low Energy Consumption ◽  
Distance Communication

Recent market studies show that the market for remote monitoring devices of different medical parameters will grow exponentially. Globally, more than 4 million individuals will be monitored remotely from the perspective of different health parameters by 2023. Of particular importance is the way of remote transmission of the information acquired from the medical sensors. At this time, there are several methods such as Bluetooth, WI-FI, or other wireless communication interfaces. Recently, the communication based on LoRa (Long Range) technology has had an explosive development that allows the transmission of information over long distances with low energy consumption. The implementation of the IoT (Internet of Things) applications using LoRa devices based on open Long Range Wide-Area Network (LoRaWAN) protocol for long distances with low energy consumption can also be used in the medical field. Therefore, in this paper, we proposed and developed a long-distance communication architecture for medical devices based on the LoRaWAN protocol that allows data communications over a distance of more than 10 km.

scholarly journals A Low-cost System for High-frequency Solar Imagery and Power Data Acquisition

2021 ◽  
Vol 1826 (1) ◽  
pp. 012082
Author(s):  
G F Bassous ◽  
R F Calili ◽  
C R H Barbosa
Keyword(s):  
Data Acquisition ◽  
High Frequency ◽  
Low Cost ◽  
Cost System
Sign in / Sign up

Export Citation Format

Share Document