New Products: U3V16Fx Step-Up Voltage Regulators

via Pololu Blog

We are excited to introduce our new compact and efficient U3V16Fx family of boost voltage regulators, which can generate higher voltages from input voltages as low as 1.3 V (the minimum startup voltage is 2.7 V, but they will operate down to 1.3 V after that). It’s awesome how much power these deliver in such a tiny package! It’s a little difficult to quickly convey the power or current capabilities of boost converters, since the output power is limited by the input current (which can be up to 2 A with this new family), but we usually care about the output current, which is inversely proportional to the ratio by which you are boosting the voltage. For instance, if you are tripling your voltage from 3 V to 9 V, the maximum possible output current would be one third of that 2 A maximum input (assuming 100% efficiency). Continuous currents will be a little lower than peaks, and once you factor in real world efficiency (typically 80-95%), you can expect these kinds of maximum currents:

Efficiency is also a bit hard to capture without a ton of graphs, but here’s an example from the 12 V version:

Typical efficiency of 12V Step-Up Voltage Regulator U3V16F12.

The U3V16x family includes seven versions with fixed output voltages ranging from 3.3 V to 15 V:

These new regulators are the same size as the popular U3V12Fx boost regulators, which we had to discontinue due to key components becoming obsolete, and they offer superior performance, so they should work as drop-in replacements for those older regulators in most applications.

Detect vandalism using audio classification on the Nano 33 BLE Sense

via Arduino Blog

Having something broken into and/or destroyed is an act that most people hope to avoid altogether or at least catch the perpetrator in the act when it does occur. And as Nekhil R. notes in his project write-up, traditional deterrence/detection methods often fail, meaning that a newer type of solution was necessary.

Unlike other glass breaking sensors, Nekhil’s project relies on a single, inexpensive Arduino Nano 33 BLE Sense and its onboard digital microphone to record audio, classify it, and then alert a property owner over WiFi via an ESP8266-01 board. The dataset used to train the machine learning model came from two sources: the Microsoft Scalable Noisy Speech Dataset for background noise, and breaking glass recorded on the device itself. Both of these were added to an Edge Impulse project via the Studio and split into two-second samples before being processed by a Mel-filterbank Energy (MFE) algorithm.

The resulting model, trained using 200 training cycles and slight noise additions, resulted in an impressive 92% accuracy, with some glass breaking samples being misclassified as mere noise. This was then exported to the Nano 33 BLE Sense as a library for use in a sketch that continually classifies incoming sounds and sends an email with the help of IFTTT if breaking glass is detected.

You can watch Nekhil’s demo video below and read more about this project here on the Edge Impulse blog.

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Binbot 9000 moves to where the trash is

via Arduino Blog

Our modern societies create a lot of garbage, which we can fortunately remove from our homes thanks to local waste management services. But the garbage people won’t come sift through your house for refuse, which forces you to utilize trash bins. Those bins never seem to be nearby when you need them, which is why James Bruton built the Binbot 9000.

The Binbot 9000 is exactly what it sounds like: a robotic trash can. No longer must the bin remain stationed in some out-of-the-way location. Instead, Binbot 9000 can drive around a home in search of people who need to throw things away.

Bruton started by placing a standard trash can on a robotic frame built using aluminum extrusion and 3D-printed parts. It has two drive wheels with encoders, which an Arduino Mega 2560 controls. To navigate through the home while avoiding collisions, Bruton added an NVIDIA Jetson Nano single-board computer and a Raspberry Pi Camera. The Jetson runs computer vision software and feeds commands to the Arduino via serial.

The computer vision software looks for simple targets printed on sheets of paper. The robot rotates until it sees and centers a target in the video frame. It will then drive forward until it reaches the target, rotates 90 degrees, and repeats the process. If it collides with something (ideally someone’s foot), the wheel encodes will detect the stall and the robot will open its lid with a servo. After someone deposits trash and closes the lid, the robot will go back into its target-seeking cycle.

By placing targets in strategic locations around his home, Bruton gave Binbot 9000 the ability to drive around his home in efficient paths. Whenever he needs to throw something away, he can nudge the robot to stop it and deposit his garbage. It also responds to voice commands, so Bruton can summon it or send it home as needed.

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This health belt can provide early warning of heart failure

via Arduino Blog

Heart disease is the most common cause of death — not just in industrialized countries, but for the world as a whole. Many deaths caused by heart failure could be prevented if the patient received medical care sooner, but people are often unaware of impending heart failure until it actually occurs. However, there are physiological indicators that become detectable in advance of heart failure. This wearable “health belt” contains sensors that monitor for those indicators to give warning of imminent heart failure so patients can seek lifesaving medical attention.

This health belt has a variety of sensors to monitor key physiological indicators, including thoracic impedance, heart rate, electrocardiogram activity, and motion activity. None of those alone would reliably correspond to upcoming heart failure without many false positives and negatives, but together they provide a clear picture. The sensor array, which is wearable and resembles a cumberbund, communicates via Bluetooth with the user’s phone. When the signs of heart failure appear, their phone can either notify them to seek medical attention or notify a third party, like a family member or doctor.

The team used an Arduino Uno board to construct their prototype health belt. It connects to several sensors: a peripheral module interface (PMOD) Impedance Analyzer (IA), an AD8232 ECG (electrocardiogram) sensor, a MAX30105 heart rate sensor, and an ADXL362 accelerometer. Power comes from a 9V battery and an HC06 module handles the Bluetooth communication. 

More testing is needed to determine the health belt’s efficacy, as the research team wasn’t able to gather data from people actually experiencing heart failure. But early testing with a subject mimicking similar body movement and breathing was promising.

Image credit: Iqbal, S.M.A., Mahgoub, I., Du, E. et al. Development of a wearable belt with integrated sensors for measuring multiple physiological parameters related to heart failure. Sci Rep 12, 20264 (2022).

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Name that Ware November, 2022

via Hacking – bunnie's blog

The Ware for November 2022 is shown below.

A grounded guard ring is placed around some of the most sensitive analog traces; I would love it if someone could teach me why the soldermask is removed for these guard rings. I imagine there must be some motivation to retain this motif even into mass production, since the mask-less traces run between SMT pins, which I have to imagine incurs a potential yield impact, or at the very least it makes rework more challenging.

Also, yet another tamper-proof seal broken:

It was just a matter of time…such is the fate of any seal within my reach!

Winner, Name that Ware October 2022

via Hacking – bunnie's blog

The Ware for October 2022 is a Wavetek Model 21 signal generator. The winner is Marc! Congrats, email me for your prize!

Here’s some more photos of the system for context. It consists of a function generator (analog) board, and a digital control board, along with a third board (not shown) that manages the LCD and buttons.