312 research outputs found
Localization in Long-range Ultra Narrow Band IoT Networks using RSSI
Internet of things wireless networking with long range, low power and low
throughput is raising as a new paradigm enabling to connect trillions of
devices efficiently. In such networks with low power and bandwidth devices,
localization becomes more challenging. In this work we take a closer look at
the underlying aspects of received signal strength indicator (RSSI) based
localization in UNB long-range IoT networks such as Sigfox. Firstly, the RSSI
has been used for fingerprinting localization where RSSI measurements of GPS
anchor nodes have been used as landmarks to classify other nodes into one of
the GPS nodes classes. Through measurements we show that a location
classification accuracy of 100% is achieved when the classes of nodes are
isolated. When classes are approaching each other, our measurements show that
we can still achieve an accuracy of 85%. Furthermore, when the density of the
GPS nodes is increasing, we can rely on peer-to-peer triangulation and thus
improve the possibility of localizing nodes with an error less than 20m from
20% to more than 60% of the nodes in our measurement scenario. 90% of the nodes
is localized with an error of less than 50m in our experiment with
non-optimized anchor node locations.Comment: Accepted in ICC 17. To be presented in IEEE International Conference
on Communications (ICC), Paris, France, 201
GNSS-free outdoor localization techniques for resource-constrained IoT architectures : a literature review
Large-scale deployments of the Internet of Things (IoT) are adopted for performance
improvement and cost reduction in several application domains. The four main IoT application
domains covered throughout this article are smart cities, smart transportation, smart healthcare, and
smart manufacturing. To increase IoT applicability, data generated by the IoT devices need to be
time-stamped and spatially contextualized. LPWANs have become an attractive solution for outdoor
localization and received significant attention from the research community due to low-power,
low-cost, and long-range communication. In addition, its signals can be used for communication
and localization simultaneously. There are different proposed localization methods to obtain the
IoT relative location. Each category of these proposed methods has pros and cons that make them
useful for specific IoT systems. Nevertheless, there are some limitations in proposed localization
methods that need to be eliminated to meet the IoT ecosystem needs completely. This has motivated
this work and provided the following contributions: (1) definition of the main requirements and
limitations of outdoor localization techniques for the IoT ecosystem, (2) description of the most
relevant GNSS-free outdoor localization methods with a focus on LPWAN technologies, (3) survey
the most relevant methods used within the IoT ecosystem for improving GNSS-free localization
accuracy, and (4) discussion covering the open challenges and future directions within the field.
Some of the important open issues that have different requirements in different IoT systems include
energy consumption, security and privacy, accuracy, and scalability. This paper provides an overview
of research works that have been published between 2018 to July 2021 and made available through
the Google Scholar database.5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira PaivaN/
Efficient vertical handover in heterogeneous low-power wide-area networks
As the Internet of Things (IoT) continues to expand, the need to combine communication technologies to cope with the limitations of one another and to support more diverse requirements will proceed to increase. Consequently, we started to see IoT devices being equipped with multiple radio technologies to connect to different networks over time. However, the detection of the available radio technologies in an energy-efficient way for devices with limited battery capacity and processing power has not yet been investigated. As this is not a straightforward task, a novel approach in such heterogeneous networks is required. This article analyzes different low-power wide-area network technologies and how they can be integrated in such a heterogeneous system. Our contributions are threefold. First, an optimal protocol stack for a constrained device with access to multiple communication technologies is put forward to hide the underlying complexity for the application layer. Next, the architecture to hide the complexity of a heterogeneous network is presented. Finally, it is demonstrated how devices with limited processing power and battery capacity can have access to higher bandwidth networks combined with longer range networks and on top are able to save energy compared to their homogeneous counterparts, by measuring the impact of the novel vertical handover algorithm
Practical Experiences of a Smart Livestock Location Monitoring System leveraging GNSS, LoRaWAN and Cloud Services.
Livestock farming is, in most cases in Europe, unsupervised, thus making it difficult to ensure adequate control of the position of the animals for the improvement of animal welfare. In addition, the geographical areas involved in livestock grazing usually have difficult access with harsh orography and lack of communications infrastructure, thus the need to provide a low-power livestock localization and monitoring system is of paramount importance, which is crucial not for a sustainable agriculture, but also for the protection of native breeds and meats thanks to their controlled supervision. In this context, this work presents an Internet of things (IoT)-based system integrating low-power wide area (LPWA) technology, cloud and virtualization services to provide real-time livestock location monitoring. Taking into account the constraints coming from the environment in terms of energy supply and network connectivity, our proposed system is based on a wearable device equipped with inertial sensors, Global Positioning System (GPS) receiver and LoRaWAN transceiver, which can provide a satisfactory compromise between performance, cost and energy consumption. At first, this article provides the state-of-the-art localization techniques and technologies applied to smart livestock. Then, we proceed to provide the hardware and firmware co-design to achieve very low energy consumption, thus providing a significant positive impact to the battery life. The proposed platform has been evaluated in a pilot test in the Northern part of Italy, evaluating different configurations in terms of sampling period, experimental duration and number of devices. The results are analyzed and discussed for packe delivery ratio, energy consumption, localization accuracy, battery discharge measurement and delay
Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation
The Internet of Things (IoT) has started to empower the future of many
industrial and mass-market applications. Localization techniques are becoming
key to add location context to IoT data without human perception and
intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN)
technologies have advantages such as long-range, low power consumption, low
cost, massive connections, and the capability for communication in both indoor
and outdoor areas. These features make LPWAN signals strong candidates for
mass-market localization applications. However, there are various error sources
that have limited localization performance by using such IoT signals. This
paper reviews the IoT localization system through the following sequence: IoT
localization system review -- localization data sources -- localization
algorithms -- localization error sources and mitigation -- localization
performance evaluation. Compared to the related surveys, this paper has a more
comprehensive and state-of-the-art review on IoT localization methods, an
original review on IoT localization error sources and mitigation, an original
review on IoT localization performance evaluation, and a more comprehensive
review of IoT localization applications, opportunities, and challenges. Thus,
this survey provides comprehensive guidance for peers who are interested in
enabling localization ability in the existing IoT systems, using IoT systems
for localization, or integrating IoT signals with the existing localization
sensors
Adaptive Geolocation of IoT devices for Active and Assisted Living
Recent developments in IoT devices and communication systems, have brought to light new
solutions capable of offering advanced sensing of the surrounding environments. On the other
hand, during the last decades, the average life expectancy has increased, which translates into a
considerable rise in the number of elderly people. Consequently, in view of all these factors, there
is currently a constant demand for solutions to support an Active and Assisted Living (AAL) of
such people.
The presented thesis intends to propose a solution to help to know the location of IoT devices
that may be assisting people. The proposed solution should take into consideration the risk factors
of the target group at each moment, as well as the technical constraints of the device, such as its
available power energy and means of communications. Thus, ultimately, a profile-based decision
should autonomously be made by the device or its integrated system, in order to ensure the usage
of the best geolocation technology for each situation.Desenvolvimentos recentes em dispositivos IoT e em sistemas de comunicação, trouxeram
consigo novas soluções capazes de oferecer uma deteção avançada dos ambientes circundantes.
Por outro lado, no decorrer das últimas décadas, a esperança média de vida aumentou, o que se
traduz também num considerável aumento do número de pessoas idosas. Por conseguinte, perante
o conjunto destes factores, existe actualmente uma procura constante de soluções de suporte a uma
Active and Assisted Living desse grupo de pessoas.
A presente tese tenciona propor uma solução que ajude a conhecer a localização dos dispositivos
IoT que possam estar a ajudar pessoas. A solução proposta deve ter em consideração os fatores
de risco do grupo-alvo em cada momento e também as restrições técnicas do dispositivo, como
a energia disponível e os meios de comunicação. Deste modo, em última instância, uma decisão
baseada num perfil deve ser tomada autonomamente pelo dispositivo ou pelo seu sistema, para
garantir a utilização da tecnologia de geolocalização mais adequada em cada situação
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