IoT based indoor location detection system for smart home environment

Nath, Rajdeep Kumar; Bajpai, Rajnish; Thapliyal, Himanshu

doi:10.1109/icce.2018.8326225

Cited by 40 publications

(21 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Chen et al [7] observed that BLE beacons had already been deployed in the retail industry, showing the proximity of items on customers' phones, and thus, creating a more engaging shopping experience. In smart life environments, Nath et al [3] proposed a voice-based location detection system that can be integrated into a smart home environment. The system is suitable for large-scale application, where a user may need to keep track of multiple patients.…”

Section: Discussion and Evaluationmentioning

confidence: 99%

“…Table 6. A comprehensive comparison of the proposed technique with the most recent techniques (adapted from [3,5,7,[28][29][30][31]).…”

Section: Discussion and Evaluationmentioning

confidence: 99%

“…In recent years, information and communication technology has rapidly advanced. In order to achieve a more convenient living environment, people have begun to install intelligent appliances that are able to transmit information in their homes, resulting in the Internet of Things (IoT) [1][2][3]. With the maturity of cloud computing and IoT technology, smart homes have become an important future trend [4].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Developing a BLE Beacon-Based Location System Using Location Fingerprint Positioning for Smart Home Power Management

Chan

et al. 2018

Energies

View full text Add to dashboard Cite

In recent years, smart homes have begun to use various sensors to detect the location of users indoors. However, such sensors may not be stable, resulting in high detection error rates. Thus, how to improve indoor positioning accuracy has become an important topic. This study explored Bluetooth Low Energy (BLE) Beacon indoor positioning for smart home power management. A novel system framework using BLE Beacon was proposed to detect the user location, and to perform power management in the home through a mobile device application. Since the BLE Beacon may produce a multipath effect, this study used the positioning algorithm and hardware configuration to reduce the error rate. Location fingerprint positioning algorithm and filter modification were used to establish a positioning method for facilitating deployment, and to reduce the required computing resources. The experiments included an observation of the Received Signal Strength Indicators (RSSI) and selecting filters and a discussion of the relationship between the characteristics of the BLE Beacon signal accuracy and the number of the BLE Beacons deployed in the observation space. The BLE Beacon multilateration positioning was combined with the In-Snergy intelligent energy management system for smart home power management. The contribution of this study is to allow users to enjoy smart home services based on their location within the home using a mobile device application.

show abstract

Section: Discussion and Evaluationmentioning

confidence: 99%

“…Table 6. A comprehensive comparison of the proposed technique with the most recent techniques (adapted from [3,5,7,[28][29][30][31]).…”

Section: Discussion and Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Developing a BLE Beacon-Based Location System Using Location Fingerprint Positioning for Smart Home Power Management

Chan

et al. 2018

Energies

View full text Add to dashboard Cite

show abstract

“…Nowadays, there is active research on the field of human body detection, indoor localization and their application for smart home appliances [13,14]. For human body detection, various sensors such as passive infrared (PIR), thermopile, and vision sensors are adopted in the home appliances.…”

Section: Related Workmentioning

confidence: 99%

Deep Neural Network Based Ambient Airflow Control through Spatial Learning

2020

View full text Add to dashboard Cite

As global energy regulations are strengthened, improving energy efficiency while maintaining performance of electronic appliances is becoming more important. Especially in air conditioning, energy efficiency can be maximized by adaptively controlling the airflow based on detected human locations; however, several limitations such as detection areas, the installation environment, and sensor quantity and real-time performance which come from the constraints in the embedded system make it a challenging problem. In this study, by using a low resolution cost effective vision sensor, the environmental information of living spaces and the real-time locations of humans are learned through a deep learning algorithm to identify the living area from the entire indoor space. Based on this information, we improve the performance and the energy efficiency of air conditioner by smartly controlling the airflow on the identified living area. In experiments, our deep learning based spatial classification algorithm shows error less than ± 5 ° . In addition, the target temperature can be reached 19.8% faster and the power consumption can be saved up to 20.5% by the time the target temperature is achieved.

show abstract

“…Pensando no crescimento da população idosa e que necessita de cuidados constantes, Nath et al (2018) desenvolveram um sistema para ser integrado nas casas inteligentes que permite localizar o paciente baseado em sua voz. Com isso, o cuidador tem informações em tempo real sobre o paciente.…”

Section: Aplicação Da Internet Das Coisas Em Casas Cidades E Redes Iunclassified

Sistema para Controle e Monitoramento de Ambientes Utilizando Internet das Coisas

Amorim

Oliveira

Machado-Coelho

et al. 2019

Anais Do 14º Simpósio Brasileiro De Automação Inteligente

View full text Add to dashboard Cite

The increase in demand for convenience and security, together with the focus on energy efficiency, has made residential automation become more relevant. One way to expand the use this technology is by applying the Internet of Things (IoT) concept, that connects things and people through wireless networks. The objective of this work is to develop a system that monitors and controls residential environments by using the IoT concept. The developed devices are independent and used in a cloud system in order to perform their tasks, which can be done remotely. Services that allow integration with external systems are available through the rest API. Resumo: Com o aumento da demanda por comodidade, segurança e o foco em eficiência energética, a automação residencial vem ganhado espaço. Uma aposta para expandir o uso desta tecnologia e melhorar a questão energéticaé a aplicação do conceito de Internet das Coisas (IoT), que interliga coisas e pessoas através de redes sem fio. O objetivo deste trabalhoé desenvolver um sistema para controle e monitoramento de ambientes utilizando o conceito de IoT. Os dispositivos construídos são independentes e estão integrados a um sistema nas nuvens para realização do procedimento, que pode ser feito de modo remoto. São disponibilizados serviços que permitem a integração de sistemas externos através de um web server criado com API rest.

show abstract

IoT based indoor location detection system for smart home environment

Cited by 40 publications

References 6 publications

Developing a BLE Beacon-Based Location System Using Location Fingerprint Positioning for Smart Home Power Management

Developing a BLE Beacon-Based Location System Using Location Fingerprint Positioning for Smart Home Power Management

Deep Neural Network Based Ambient Airflow Control through Spatial Learning

Sistema para Controle e Monitoramento de Ambientes Utilizando Internet das Coisas

Contact Info

Product

Resources

About