Monthly Archives: April 2025

Enhanced Security with SOS-enabled BLE Badge

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Enhancing Staff Security with BLE Badge Featuring SOS Buttons

Imagine what would a dedicated nurse devoted to the patients and the hospital expect at minimum from the management?
Surely she would expect that her safety and security are taken care of while she is inside hospital.
Healthcare workers are often required to walk throughout the facility, sometimes in high-risk situations, and their safety should never be compromised. A practical, efficient solution to improve staff security is the introduction of BLE-enabled ID badge or BLE wristbands equipped with SOS buttons, offering a simple yet powerful way to alert security in moments of distress. BLE-enabled badge works for dual-purpose : as an ID badge as well as safety SOS device.

BLE Wristbands

BLE wristband with SOS buttonBluetooth Low Energy (BLE) technology allows for seamless, low-energy communication over short distances, making it ideal for environments like hospitals where staff are constantly on the move. A BLE wristband with an integrated SOS button ensures that the wearer can discreetly and instantly alert security personnel in the event of an emergency, regardless of their location within the hospital.

Patient Safety and Location Tracking

The wristband can be used for patients too. The wristband enables the hospital locate the patient in real-time when in need. It also enables the Patient to alert the nurse-station when in need. Pressing the SOS button sets off a buzzer in the nearest nurse station. It also flashes the location of the patient in App notification.

App Alerts for Immediate Response

A RTLS works in tandem to ensure that information flows in real time. The wristband SOS enables the staff send an immediate notification to the hospital security teams at the push of a button. Once activated, the SOS button triggers an alert, pinpointing the exact location of the distressed staff member within the facility. This swift communication allows security to respond faster, reducing the time it takes to reach the scene of an emergency.

Empowering Staff to Feel Secure

One of the most significant benefits of the wristband is the psychological comfort it provides. Knowing that help is just a button press away can make staff members, particularly women, feel more secure while performing their duties. They can focus on their work without constantly worrying about their safety, knowing that help is easily accessible in any situation—whether it’s an incident of harassment, a medical emergency, or a physical threat.

Discreet and Non-Intrusive

The Badge is designed to be lightweight, discreet, and comfortable, ensuring that staff can wear it throughout their shift without feeling encumbered. The SOS button is intuitive to use, and its small form factor allows it to blend seamlessly into the work attire of hospital staff. This non-intrusive nature ensures that it does not interfere with daily tasks but remains within easy reach in moments of need.

Building a Safer Work Environment

By adopting BLE wristbands with SOS buttons for all hospital staff, we create a safety net that reinforces the hospital’s commitment to employee well-being. This proactive measure is an investment in a safer, more supportive work environment where staff can feel protected and valued. In an unpredictable workplace like a hospital, staff members deserve the peace of mind that comes from knowing that their safety is a priority.

RFID or BLE for your Hospital RTLS?

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BLE or RFID? - Things to consider before you decide for your hospital

A hospital RTLS primarily is a software that uses wireless technologies e.g. RFID, BLE or UWB, to provide you real time indoor location intelligence (for example, which asset is currently in which zone?) for your hospitals. Most RTLS vendors tie their software to a specific technology, which means deciding vendor itself selects the technology. But is the optimal? Would you not like to understand the cost-benefits independently before you let your vendor choose for you?

When it comes to hospital RTLS, hospitals in US have predominantly adopted RTLS based on RFID though cost is very high. It's also true that RFID (especially active RFID) based RTLS is there for a very long time. BLE in fact is a recent addition. Interesting thing is both BLE and active RFID uses 2.4 GHz band but while BLE standard is open, active RFID is often proprietary and therefore costlier.

Understanding RFID

RFID is wireless radio frequency (RF) based standard and works on multiple RF bands, designated as LF (Low Frequency), HF (High Frequency) and UHF (Ultra High Frequency). Accuracy and speed increases from LF to UHF. Main components of this technology is RF Tag, RF Antenna and RF Readers. RF Tag can be active which means the tag has a battery and sends data on its own. Passive RF tag on the other hand is without battery and it can only send the data using the reflected RF energy (from the reader). The advantage of passive RF Tag is that it has almost unlimited life (no battery replacement) and also costs 10 times less than an active RF tag. To read passive RF Tags, the RFID reader must use high-gain antenna.

UHF RFID operates at 860-930 MHz (For India designated band is 865-867 MHz) but the high gain makes it a little unattractive to use in radio-sensitive places inside the Hospital.

RFID protocols were designed for reading inventory which makes it little difficult to employ it for indoor location tracking in real time. Given the high cost of UHF RFID readers (above USD 1,000), building RFID infrastructure for a hospital is often prohibitively expensive. While most leading vendors started supporting WiFi in the their RFID readers in latest products, old models typically do not support WiFi, which means it needs its separate network making the installation expensive. For a medium-sized hospital, RFID infrastructure costs have been reported between $200,000 and $600,000, depending on the facility's size and specific requirements.

Due to high cost, a hospital typically uses only a few fixed Reader placed at strategic location to cover entire floor area. But that also brings down effectiveness of tracking. Large inaccuracy of location with RFID based RTLS is a common refrain.

How BLE is different?

Most Hospital RTLS employs active RFID hardware which typically uses the regulation-free 2.4GHz. This is the same frequency band that is used in Microwave Ovens all over the world, as well as Bluetooth Devices and basic WiFi network. Given the low power gain used, it is considered safe.
BLE stands for Bluetooth Low Energy and is used in sensor network ubiquitously. Being lightweight, the devices come with very small form factor.  BLE works in the same way as active RFID. But since BLE standard is open, BLE devices have proliferated a lot faster. That effectively has brought down the cost of BLE tags and BLE gateways. BLE gateways cost 10 times lesser than a RFID reader and it can use the hospital's WiFi network which  in turn brings down the overall installation cost for BLE based RTLS.

For a 40 room hospital, it was reported to cost below USD 100K. However, we should remember, the cost of BLE tags are higher compared to passive RFID tags and battery of a BLE tag typically needs replacement every 1-2 years.

Active RFID vs BLE

Both of them need battery which means it requires periodic battery replacement. Additionally active RFID devices and tags are relatively more costly. More importantly vendor lock-in is one major aspect of using active RFID hardware. In comparison BLE devices are available off-the-shelf and can be upgraded / replaced with different vendor's products at ease without any service downtime.

A ready comparison chart

Feature UHF RFID BLE
Frequency Band 860–956 MHz 2.4 GHz
Range Up to 100 meters (depending on tag and reader / antenna)  less than UHF RFID
Data Rate Up to 640 kbps Up to 2 Mbps
Accuracy Typically within a margin of a few meters. Passive tags sometimes are missed by the Readers during periodic scanning Better than RFID. BLE Tags send the data themselves - eliminating the issue of missed scans.
Power Consumption Passive tags require no power; active tags have batteries Low power consumption; suitable for battery-powered devices
Cost Passive tags are cost-effective; active tags are more expensive Generally low-cost due to widespread adoption
Typical Applications Asset tracking, inventory management, supply chain logistics Asset tracking, personnel monitoring, proximity marketing, indoor navigation
Tag Cost Passive UHF RFID tags: Approximately $0.10 to $0.50 per tag.
Active RFID tags: Approximately $5 to $15 per tag.		 BLE tags: Approximately $2 to $10 per tag.
Reader/Gateway Cost Fixed RFID readers: Approximately $1,400 to $8,000 per unit.

Handheld RFID readers: Approximately $1,000 to $4,500 per unit.

 BLE gateways: Approximately $100 to $500 per unit.

INDTRAC Approach

INDTRAC promises to work with almost all leading BLE and passive UHF RFID readers. INDTRAC also qualifies vendor hardware before they are recommend to you so that you can choose the technology most suited for your use case and budget without any worries. For BLE tags, INDTRAC proactively monitors the battery and alerts you to replace the battery when a tag battery loses the power. BLE tags mostly use ubiquitously available low-cost coin lithium battery which makes the replacement cost very marginal.
There is another advantage with using BLE -- you can seamlessly use the RTLS to monitor zone-wise temperature, humidity or VOC almost at the same expense as that of asset tracking infrastructure.

Responsible AGI and other things

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Google apparently in recognition that they lost LLM game (first to OpenAI chatgpt and then to Chinese deepseek) started drum rolling for AGI. Given how people are afraid of AGI, they brought out a paper on responsible AGI (somewhat similar to earlier responsible AI ). Read the Google post here.

Does it mean that LLM ≠ AGI

There were posts earlier where OpenAI said chatgpt is almost AGI. Even some in Google Gemini team said Gemini is almost sentient. But if people are talking about AGI seperately from LLM, perhaps that is acceptance of that fact that LLM may not ever reach human capability of intelligence. In fact there was a recent study that asserted that LLM could not match human ingenuity of ‘zero shot abstract thinking’.
Martha Lewis, a coauthor of the study, tells LiveScience, – while we can abstract from specific patterns to more general rules, LLMs don’t have that capability. “They’re good at identifying and matching patterns, but not at generalizing from those patterns.”  Read the full LiveScience post.

Can the AGI be responsible?

AGI has to evolve from current generative AI framework. Google Deepmind has categorized the challenge into four baskets:

  • Misalignment
  • Misuse
  • Mistake
  • Structural Risk

Misalignment refers to AI model doing something that developers did not intend it to do. Misuse refers to the model being misused by a human controller/user to work as adversary to humanity. Mistake refers to AI model doing something bad without triggering internal checks and balances. Structural Risk ensues from multi-agent dynamics without any fault from individual model. Example for this can be, a new path opens up due to complex interlinking of activities between AI models which developers didn’t intend to.

Of all the four types, Misalignment and Structural Risk are the most difficult to address because they are the most complex and difficult to uncover. We will limit ourselves to the issue of Misalignment for this post. Marcus Arvan explained in a LiveScience post, ‘If any AI became ‘misaligned’ then the system would hide it just long enough to cause harm’. He has given real life examples where LLM shocked the user with the answers.

‘The basic issue is one of scale. Consider a game of chess. Although a chessboard has only 64 squares, there are 1040 possible legal chess moves and between 10111 to 10123 total possible moves — which is more than the total number of atoms in the universe. This is why chess is so difficult: combinatorial complexity is exponential.

LLMs are vastly more complex than chess. ChatGPT appears to consist of around 100 billion simulated neurons with around 1.75 trillion tunable variables called parameters. Those 1.75 trillion parameters are in turn trained on vast amounts of data — roughly, most of the Internet. So how many functions can an LLM learn? Because users could give ChatGPT an uncountably large number of possible prompts — basically, anything that anyone can think up — and because an LLM can be placed into an uncountably large number of possible situations, the number of functions an LLM can learn is, for all intents and purposes, infinite.’ He argues.

Google’s approach to tackle misalignment

Google plans to use second AI model to validate a model’s answer. It’s sort of AI police to police AI model. Can this work? To find answer, we should ask, does policing work for human citizens? You could say mostly. But we should not miss that mostly it’s willingness of human citizens to follow rule and respect police that makes the job of police manageable. We surely cannot assert that for AI citizens. But given that entire AI paradigm works on goal-seeking principle, meticulous control of goal dynamics may provide an understanding of AI motivation.
Demis Hassabis, the Nobel Laureate CEO of DeepMind has a sobering thought about the approach to AGI. In a lecture in Cambridge University, he said, “Lot of Silicon Valley Companies work with the principle of ‘Move Fast, Break Things’ but I think it is not appropriate, in my opinion, for this type of transformative technology. I think instead we should be trying to use scientific method and approach with humility and respect this kind of technology deserves. We don’t know lot of things. Lot of unknowns about how this technology is going to develop. With exceptional sort of care and foresight we can get all the benefits and minimize the downside of it.” He invites people to focus on research and debate now and be mindful that the technology does not really go out of hand.
We are with him on that thought.