Author: Support

Improving RSSI Using Relabelling

Researchers from Japan have a new Relabelling Approach to Signal Patterns for Beacon-based Indoor Localization in Nursing Care Facility. Bluetooth beacons were used in a nursing care facility to enhance the tracking and location estimation of caregivers. These beacons were strategically placed throughout the facility, particularly outside patient rooms and in common areas. The caregivers carried smartphones with a mobile application called FonLog installed, which recorded the Received Signal Strength Indicator (RSSI) readings from the beacons and logged location labels.

The beacons were set to a frequency of 10 Hz with a coverage range of up to five meters. The main challenge addressed in this study was the signal loss and limited data, which affected the accuracy of indoor localisation. To improve the data quality, a relabelling approach was applied. This involved observing the signal patterns in different rooms and using these patterns to augment the training data by relabelling RSSI values from one location as samples for another location with low data samples.

This approach aimed to increase the dataset and improve the model’s accuracy in recognising the caregivers’ locations. By doing so, the accuracy of the indoor localisation model improved, achieving an accuracy of 74%, which was a 5% improvement over the original data. The use of Random Forest for location recognition further enhanced the performance, demonstrating the effectiveness of combining relabelling with machine learning techniques for indoor localisation in a healthcare setting.

New Nordic Semiconductor Wireless Quarter

Nordic Semiconductor, the leading manufacturer of System on a Chip (SoC) used in most beacons and the top supplier of SoCs for Bluetooth LE solutions, has released the latest PDF edition of Wireless Quarter Magazine. This issue highlights the diverse applications of Nordic’s SoCs.

The latest issue of the magazine highlights the increasing use of the Nordic SoCs in health. There are details on a smart ring that delivers non-invasive diabetic risk assessment and a Bluetooth LE hybrid smartwatch that delivers accurate health data.

There are also in-depth articles on how Bluetooth is transforming the industrial Internet of Things, the smart home and precision air quality monitoring. There’s also news that the nRF Connect SDK now supports Google’s Find My Device network.

Using Beacons to Understand Social Drinking

A new study Detecting and Understanding Social Influence During Drinking Situations: Protocol for a Bluetooth-Based Sensor Feasibility and Acceptability, from Brown University United States, evaluates the feasibility and acceptability of using Bluetooth beacons and a smartphone app to measure social interactions in real-world drinking situations among young adults. The background of the study highlights that high-risk drinking often occurs in social settings among peers and the objective was to explore how Bluetooth-based sensors could detect real-time social interactions during drinking events. This data could then inform just-in-time interventions to mitigate risky behaviours.

Participants in the study included 20 young adults who engage in heavy social drinking. Each participant was asked to recruit three friends to carry Bluetooth beacons. These beacons emitted Bluetooth signals detectable by the participants’ smartphones, and a specialised smartphone app triggered reports based on the proximity of these beacons. The data collection was facilitated through Ecological Momentary Assessment (EMA), which involved random, signal-contingent, and morning reports to gather information on alcohol use and social interactions. Reports were triggered when a beacon came within 15 feet of a participant for at least 15 minutes.

During the EMA protocol, participants completed different types of reports. Signal-contingent reports were triggered by the app when a peer’s beacon was detected nearby. Random reports were issued three times daily at random intervals to capture spontaneous interactions and behaviours. Morning reports collected daily data on the previous day’s activities and first-drink reports were initiated by participants when they began drinking.

The implications of the study’s findings are significant. They could inform the development of interventions that provide real-time feedback and support to individuals in high-risk drinking situations, potentially reducing alcohol-related harms. The use of passive sensing technology, such as Bluetooth beacons, enhances the effectiveness of just-in-time interventions by accurately detecting social contexts that influence drinking behaviour.

Beacons are a Technology, Not the Solution

There’s an interesting app/service called Voolsy, in India, that uses iBeacons to enable a slick restaurant mobile app. The key thing here is that beacons are mentioned just once on their web pages. The emphasis is, instead, on making it “easy to place order & pay bills”.

Take a look at your current and proposed beacon-based solution and see if you can remove almost all references to beacons and instead concentrate on the problem being solved for your users. That way you are more likely to engage customers and less likely to alienate them with what’s, to them, incomprehensible technology. Beacons are an enabling technology, not the solution.

Customers are primarily interested in how a product or service can solve their problems or meet their needs. Emphasising the solution simplifies communication, making it easier for customers to understand and appreciate the benefits.

Enhancing Behavioral Health Monitoring Through Bluetooth Proximity Detection

New research by researchers from Department of Behavioural and Social Sciences Brown University, USA looks into A Bluetooth-Based Smartphone App for Detecting Peer Proximity: Protocol for Evaluating Functionality and Validity.

The study describes a Bluetooth-based smartphone app designed to detect the physical proximity of peers, particularly to monitor health behaviours like alcohol consumption. The app uses Bluetooth beacons and aims to improve upon traditional Ecological Momentary Assessment (EMA) by reducing reliance on participant self-reporting through the passive detection of social interactions.

The primary objective is to develop and validate a system using Bluetooth beacons to passively detect when two or more individuals are in close proximity. The methodology involves 20 participants aged 18-29 years, using a smartphone app to collect data over three weeks. Participants’ influential peers carry Bluetooth beacons, and the app records when beacons come into proximity.

The technology could have significant applications in monitoring and intervening in health behaviours by providing real-time, accurate data on social interactions that influence these behaviours. This could be particularly useful in developing “just-in-time” adaptive interventions targeted at high-risk behaviours as they occur.

Results from the study are expected to be reported by 2025, with potential implications for enhancing the accuracy and efficacy of behavioural health interventions. The technology and methodology developed could be applicable to a broader range of behaviours and settings where social context plays a critical role in health outcomes.

New KKM Waterproof Sensor Beacon

We have the new, waterproof sensor beacon S5 in stock.

This beacon measures temperature, humidity and 3-axis acceleration. It also logs up to 60,000 temperature and humidity records, viewable in the manufacturer’s app. It has a 180m range and also supports Bluetooth 5 coded PHY, when supported by the receiving device, for a longer range of 600m. It’s also the only beacon we know of, that comes with a temperature/humidity calibration certificate.

Inovalon Uses Bluetooth iBeacons

Inovalon is a leading provider of cloud-based software solutions focused on data-driven healthcare. Their Inovalon ONE® Platform integrates national-scale connectivity, real-time primary source data access and advanced analytics to improve clinical outcomes and economics across the healthcare ecosystem. It is used by over 20,000 customers, informed by data from more than 78 billion medical events.

The platform uses Bluetooth beacons as part of its healthcare time and attendance management system. These beacons help in accurately tracking employee attendance and location within healthcare facilities, ensuring efficient workforce management. For more details, visit Inovalon’s website.

Solar Powered Bluetooth Bluetooth Beacons

While we previously sold solar powered Bluetooth beacons, we have been reflecting on why they never gained widespread adoption.

Solar iBeacon

Cost and Complexity: Solar panels and related hardware add to the cost and complexity of Bluetooth beacons. This makes them more expensive to produce compared to battery-powered alternatives.

Reliance on a Rechargeable Battery: In order to keep working under temporary poor lighting, a rechargeable battery can be included in the design. This battery, itself, has a limited physical lifetime and will eventually need replacing.

Reliability: Solar power is dependent on environmental conditions. Inconsistent sunlight exposure can affect the reliability and performance of the beacons, especially in indoor or shaded areas where they might not receive enough light to function properly or to recharge an internal rechargeable battery.

Limited Use Cases: The primary use case for Bluetooth beacons is in locations where they can consistently operate without frequent maintenance. Battery-powered beacons, with their long-lasting, 5 yr+, batteries, already serve this need effectively. Modern Bluetooth beacons are designed to be highly energy-efficient, lasting a long time on a single battery. This diminishes the need for an additional/alternative power source like solar energy.

Market Demand: The demand for solar-powered solutions in the Bluetooth beacon market was always low. Businesses prefer established and reliable battery-powered beacons, reducing the incentive for companies to invest in solar-powered alternatives.

These factors combined to limit the appeal and practicality of solar-powered Bluetooth beacons, leading to their limited adoption in the market.

Survey of Bluetooth Indoor Localisation

Recent research provides a detailed survey on Bluetooth indoor localisation. The paper underscores the importance of indoor localisation and the unique challenges it presents, such as the inability of GPS to function indoors.

There’s an overview of the types of localisation methods, including triangulation, scene analysis and proximity, as well as the metrics used in these systems. The main localisation techniques discussed are RSSI (Received Signal Strength Indicator), CSI (Channel State Information), fingerprinting and other methods like Angle of Arrival (AoA) and Time of Flight (ToF). RSSI is widely used in Bluetooth localisation but suffers from poorer accuracy due to environmental factors. In contrast, CSI is rarely used due to protocol limitations. Fingerprinting is sometimes employed, involving the pre-collection of measured signal strengths to create a database for location matching.

The survey identifies issues affecting Bluetooth indoor localisation systems, such as accuracy, latency, coverage range, cost and security. Accuracy can be problematic in complex indoor environments, which introduce obstacles and multipath effects that negatively impact signal transmission and reception. The range of coverage is crucial, especially in large indoor spaces where fewer reference nodes are preferred. Cost considerations include both equipment and setup costs, and security issues arise due to the need to protect location data within personal networks.

The study summarises various existing approaches to Bluetooth indoor localisation, categorising them based on their robustness to environmental changes. In discussing RSSI versus fingerprinting, the survey notes that RSSI-based approaches are prevalent due to their simplicity and widespread use. Fingerprinting, on the other hand, involves creating a detailed database of data, which can provide more accurate localisation but requires substantial pre-processing and regular re-calibration to remain effective. Fingerprinting is susceptible to dynamic changes in the environment, making it less competitive in typically fluctuating conditions such as changes in room layout or occupancy.

GATT Connections and Battery Life

Our battery use power testing uncovered some cases where the battery current use during advertising was such that the battery would last longer than manufacturer specification. What was going on?

After contacting the manufacturers, it turned out that some of them include a degree of configuration activity in their battery life estimates. If you only measure the current during advertising then you haven’t taken into account the extra current used during configuration. Configuration via manufacturer apps connects, rather than just listens, to the beacon via Bluetooth GATT. GATT connections consume significantly more power. For one off configuration this will be negligible but if you are in the habit of repeatedly changing the beacon configuration then the battery life will be impacted.

The same goes for platforms/apps that periodically connect to beacons to read, change or monitor beacon parameters. The battery won’t last as long. It’s also for this reason, it’s preferable to read sensor beacon sensor data in advertising data rather than via GATT when this is supported by the beacon and your scenario can cope will less frequently reported data.