Enhancing Indoor Localisation for Ambient Assisted Living

New research Simplified Indoor Localisation Using Bluetooth Beacons and Received Signal Strength (RSSI) Fingerprinting with Smartwatch, introduces an innovative system for indoor localisation using Bluetooth Low Energy beacons and smartwatches, aimed at simplifying the process for users. This system is designed to detect a user’s location within specific areas like rooms within a house, rather than providing exact coordinates, with a particular focus on applications in ambient assisted living, especially for the elderly.

The study presents the methodology, implementation, and evaluation of the system, highlighting its practicality for real-world applications. The system demonstrated high accuracy, achieving 92.1% in environments with five rooms and 85.9% with three rooms, showcasing its effectiveness. The setup process is streamlined to reduce the number of reference points and employs a straightforward nearest neighbour algorithm, which simplifies the use and maintenance for users who may not have extensive technical skills.

The use of common and low-cost hardware components, such as Raspberry Pi for beacons and commercial smartwatches, helps keep the system affordable and simple to manage. Calibration is quick and efficient, which is ideal for residential settings. Despite its current effectiveness, the research suggests there is room for improvement. Future enhancements might include the adoption of multiple reference points per region to refine accuracy, particularly in transitional spaces between rooms.

This system offers a robust solution for indoor localisation with significant implications for healthcare, particularly aiding elderly individuals to live independently while ensuring their safety and mobility within their homes.

Indoor Locating Using Beacons in Nursing Care

The new paper Relabeling for Indoor Localization Using Stationary Beacons in Nursing Care Facilities by Christina Garcia and Sozo Inoue from the Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Japan, presents a study on enhancing machine learning for indoor localisation in caregiving, specifically in nursing homes, using Bluetooth Low Energy (BLE) technology.

The study addresses the challenge of limited data available for training machine learning models in indoor localisation, which is critical for monitoring staff-to-patient assistance and managing workload in caregiving environments. The authors propose a data augmentation method that repurposes the Received Signal Strength (RSSI) from various beacons by re-labeling them to locations with fewer data samples, thus resolving data imbalances. This method uses standard deviation and Kullback–Leibler divergence to measure signal patterns and find matching beacons for re-labeling. Two variations of re-labeling are implemented: full and partial matching.

The performance of this method is evaluated using a real-world dataset collected over five days in a nursing care facility equipped with 25 Bluetooth beacons.

Overall, the study highlights the effectiveness of the proposed re-labelling method in enhancing indoor localisation accuracy in nursing care facilities, providing a valuable contribution to the field of caregiving and workload management.

Indoor Tracking of Individuals with Mild Cognitive Impairment

There’s new research from the USA on Indoor Localization using Bluetooth and Inertial Motion Sensors in Distributed Edge and Cloud Computing Environment (PDF). The paper describes a low-cost, scalable, edge computing system for tracking indoor movements in a large indoor facility. The system uses Bluetooth Low Energy (BLE) and Inertial Measurement Unit sensors (IMU) and is designed to facilitate therapeutic activities for individuals with Mild Cognitive Impairment.

The implementation involved instrumenting a facility with 39 edge computing systems and an on-premise fog server. Subjects carried BLE beacon and IMU sensors on-body. The researchers developed an adaptive trilateration approach that considered the temporal density of hits from the BLE beacon to surrounding edge devices to handle inconsistent coverage of edge devices in large spaces with varying signal strength. They also integrated IMU-based tracking methods using a dead-reckoning technique to improve the system’s accuracy.

The conclusions of the study showed that the proposed system could robustly localise the position of multiple people with an average error of 4 meters across the entire study space, also showing 87% accuracy for room-level localisations. The integration of IMU-based dead-reckoning with Bluetooth-based localisation further enhanced the system’s accuracy.

Using Beacons to Mitigate Staff Duress

Staff duress, also known as employee duress or worker duress, is where employees may feel threatened, intimidated, or unsafe while performing their job duties. This can occur in a variety of industries, including healthcare, education, retail, hospitality, and security.

Problems associated with staff duress include:

  • Employee safety: If employees feel threatened or unsafe, it can have a negative impact on their well-being, job satisfaction, and productivity.
  • Employer liability: Employers have a legal obligation to provide a safe working environment for their employees. Failure to do so can result in legal action and financial penalties.
  • Costly incidents: If an employee is injured due to a safety issue, it can result in costly workers’ compensation claims, lawsuits, and reputational damage to the employer.

Beacons with buttons, used with real time locating systems, can help mitigate staff duress by providing a quick and effective way for employees to signal for help in an emergency situation. These devices have a wearable or handheld button that employees can press to trigger an alert. The alert is then sent to a designated response team, who can quickly assess the situation and provide assistance as needed.

Beacons with buttons can be especially useful in industries where employees work alone or in remote locations. They can also be helpful in schools and universities, where teachers and staff members may be at risk of violence or other safety threats.

Beacons with buttons

Minew B7 In Stock

We now supply the Minew B7 wearable wristband beacon.


This waterproof (IP67) beacon offers the usual iBeacon and Eddystone advertising as well as acceleration sensing. This can be via x y z in the advertising or for motion triggered broadcast. This beacon is also one of the few that also has an NFC chip for additional RFiD-based sensing. The button can be used for on/off as well as button triggered broadcasting in situations such as lone working or SOS.

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W7 Security Beacon

We have the new W7 security beacon in stock, suitable for use in places such as hospitals and prisons. It’s fitted with a security screwdriver and advertises an alert if the wristband is removed or cut off.

W7 Beacon

The W7 advertises iBeacon and Eddystone as well as acceleration (x y z) and body temperature. It’s waterproof to IP67 and is rechargeable via magnetic USB cable. The battery lasts up to a year on one charge, depending on settings.

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Using Beacons for Disability Location Determination

Researchers in Japan have been using iBeacons with children with PIMD/SMID’s expressive behaviours. These are children with profound intellectual and multiple disabilities or severe motor and intellectual disabilities who can only communicate through movements, vocalizations, body postures, muscle tensions or facial expressions.

The researchers created a system to interpret the expressive behaviours. The system uses the ChildSIDE in app to collect behaviours of children and sends the location and environmental data to a database. The beacons allow the location to be known so that displays or interfaces can be automatically changed depending on the context. For example, a specific situation (e.g. class or playtime), location (e.g. classroom, playground, home) or time (e.g. morning, lunch breaks, evening) can be determined.

ChildSIDE provides an effective method of collecting children’s expressive behaviours with a high accuracy rate in detecting and transmitting environmental and location data.

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Warning System for Home Monitoring

There’s new research into a home people tracking system to detect people who are isolated at home. The context is home isolation due to Covid but this could equally be used for people with limited mobility who need to stay indoors.

The idea is to use Bluetooth rather than visual, camera-based monitoring. Smart bracelets are used that can also monitor position, blood oxygen and heart rate.

The system can also send early warning signals to organisations or relatives through instant messaging software.

The system is implemented using ESP32 single board computers and a Raspberry Pi for data collection.

This uses MQTT, Node-Red and a database.

View Wearable Beacons

Bluetooth Vehicle–Pedestrian Collision Warning

There’s recent research by Carleton University, Ottawa, Canada on Investigating Wi-Fi, Bluetooth, and Bluetooth Low-Energy Signal Characteristics for Integration in Vehicle–Pedestrian Collision Warning Systems.

The paper looks into the comparative performance of Wi-Fi, Bluetooth Classic (Bluetooth) and Bluetooth Low Energy (BLE) for integration in vehicle–pedestrian collision warning systems. More specifically, accuracy and functionality are considered with respect to signal strength indicator (RSSI) distance stability, rainfall effects on the signals, motion effects, non-line of sight effects and signal transmission rates.

The experiments identified the overall superiority of Bluetooth LE over Wi-Fi and Classic Bluetooth. Bluetooth LE provides fast collision warnings due to the frequent transmission and provides higher probability of simultaneous signal detection by multiple scanners.

The researchers say the results indicate the possibility of integration of Bluetooth LE technology in the design of vehicle–pedestrian collision warning systems in addition to currently used systems.

Bluetooth Aiding Accessibility

We recently came across RightHear, an app that assists people with orientation difficulties or vision impairments. It provides navigation information in indoor and outdoor settings.

The app acts as a virtual directory for users, directing them through locations with audio cues (such as ‘reception is 20 feet ahead to the left’ or ‘exit is 50 feet ahead’). Users can point their phone in a specific direction to learn what’s in front of them.

For companies, the app improves accessibility compliance, aids corporate responsibility and improves a brand’s narrative regarding inclusion. It works using Bluetooth beacons that are picked up by the app. The app creates auditory descriptions and notifications. There’s also a dashboard for companies/admin to control and track the solution.

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