Hidden Raspberry Pi Projects You Never Knew Were Possible (2025)

Raspberry Pi projects have evolved into something extraordinary that goes way beyond basic coding exercises. This tiny microcontroller amazes me with its computer-like capabilities. Python programming language runs seamlessly on it and creates endless possibilities for hardware hacking. The Raspberry Pi community shows incredible creativity through luxury automated cat houses and creeper robots with camera vision.

Cool Raspberry Pi projects await your exploration, regardless of whether you use the latest Raspberry Pi 5 or an older model. The best projects often merge everyday objects with unexpected automation. A remote fish tank control system serves as a perfect example. It uses a Pi camera on a motorized platform that enables remote monitoring and management. These tiny computers keep impressing me with each new application.

Eight hidden Raspberry Pi projects will expand what you thought was possible. You’ll see everything from AI-powered plant monitors to invisible displays that use optical illusions. These projects showcase more than technical excellence. They demonstrate why Raspberry Pi has become the preferred platform for makers and tinkerers worldwide through their practical applications.

Raspberry Pi Smart Mirror with Voice Assistant

The magic mirror concept has evolved from sci-fi fantasy to a weekend Raspberry Pi project you can build yourself. These smart mirrors show your daily schedule, home system monitors, and even cheerful compliments as you get ready for your day. The best part? You can control everything hands-free with voice assistant integration.

How it works

The smart mirror illusion uses a clever optical trick with two-way acrylic. The mirror appears normal from the well-lit side, but becomes transparent from the darker side behind it. A display powered by the Raspberry Pi sits behind this special mirror. Dark backgrounds ensure only bright text and graphics shine through.

The display needs a brightness rating of at least 300 nits (cd/m²) ^[1] for the best visibility. Higher contrast between dark backgrounds and bright elements creates that perfect «floating information» effect that makes smart mirrors so fascinating.

The Raspberry Pi runs in «kiosk mode» and boots straight into a full-screen application without any computer interaction ^[1]. This setup creates a natural experience where technology fades away and only the information remains visible.

Hardware and software used

You’ll need these components to build a voice-enabled smart mirror:

• Raspberry Pi: Most builders use Raspberry Pi 3 or newer (the Pi 0/1 is not supported for full implementations) ^[2]
• Two-way mirror: Either acrylic mirror or mirror-tinted glass film applied to regular glass
• Display: An ultra-thin monitor (15.6-inch 1080p displays work well) ^[1]
• Voice assistant hardware: Microphone array (the PlayStation Eye is recommended for its four-microphone array at an affordable price) ^[3]
• Optional: Speakers, LED strips for ambient lighting

MagicMirror², an open-source modular framework, serves as the software backbone for most smart mirrors. You can install this platform with a simple command:

bash -c "$(curl -sL https://raw.githubusercontent.com/MichMich/MagicMirror/master/installers/raspberry.sh)"

You have several options for voice control:

1. Amazon Alexa: Integrates using the Alexa Voice Service (AVS) ^[4]
2. Google Assistant: Implemented through the Google Assistant SDK ^[4]
3. Mycroft AI: An open-source alternative for privacy-conscious builders ^[4]

Each voice assistant needs additional setup, but they all deliver that futuristic experience of asking your mirror for information or controlling your smart home devices.

Adding custom widgets

MagicMirror²’s modular design makes it incredibly versatile. The system includes pre-installed modules like clock, calendar, weather, news feed, and compliments ^[5]. The real excitement comes from exploring hundreds of community-built modules.

Here’s how to add a module:

1. Navigate to the modules directory: cd ~/MagicMirror/modules
2. Clone the module repository: git clone [module-repository-url]
3. Install dependencies: cd [module-name] && npm install
4. Configure the module in your config.js file

Each module needs specific settings in the config.js file. Here’s a simple example that adds a custom image module:

{
  module: "MMM-EasyPix",
  position: "top_right",
  config: {
    picName: "logo.svg",
    maxWidth: "100%",
  }
},

Popular additions include stock prices, local transportation schedules, and even Minecraft server performance monitors ^[6]. Weather information requires a free OpenWeatherMap account to get an API key ^[6].

You can enhance your mirror’s voice interaction capabilities by adding the MMM-GoogleAssistant and MMM-Detector modules ^[7]. This combination enables sophisticated voice commands that control both the mirror and your smart home devices.

Privacy-conscious users should consider local voice processing options. Advanced setups can use machine learning to detect when someone looks at the mirror. This activates the display only when needed, which saves energy and enhances the magical effect ^[8].

Smart mirrors showcase why these tiny Raspberry Pi computers have captured makers’ imagination. They combine practical daily information with smart home control in an elegant package that brings useful technology and sleek design together perfectly.

AI-Powered Plant Health Monitor

Plant health monitoring stands out as one of the most practical Raspberry Pi projects for hobbyists and serious gardeners alike. Traditional visual inspection methods can be subjective and time-consuming. Raspberry Pi-based systems now offer quick, objective analysis through cameras and sensors that detect problems before they become visible.

Using camera and sensors to detect plant stress

A good plant monitoring system needs both visual and environmental sensors. The camera module (like the Raspberry Pi V2 8MP camera) sits at the core of this Raspberry Pi project and takes regular plant images ^[9]. These images help analyze subtle changes in leaf color, texture, and overall plant growth.

Advanced setups go beyond cameras and use specialized sensors:

• NIR spectrometer sensor (AS7263): Measures near-infrared light reflection to calculate plant health using the Normalized Difference Vegetation Index (NDVI) ^[10]
• Capacitive soil moisture sensors: Last longer than resistive sensors because they don’t have exposed electrodes that corrode ^[11]
• Temperature and humidity sensors: Keep track of vital environmental conditions ^[12]
• Light sensors: Track sunlight intensity changes to optimize artificial lighting ^[13]

The sensors work best together. The NDVI calculation uses a simple formula: NDVI = (NIR – Red) / (NIR + Red), giving values between -1 and +1. Healthy plants show values from 0.2 to 0.8, while readings above 0.7 might point to dry leaves ^[10]. This scientific method turns a simple Raspberry Pi project into a smart monitoring system.

Training a simple AI model

AI makes plant monitoring better by spotting stress patterns humans might miss. Raspberry Pi projects with AI have several proven approaches.

Deep learning processes images through multilayer neural networks with weights and biases ^[9]. GoogLeNet showed remarkable results with 92.9% accuracy for wheat and 97.9% for maize in water stress detection ^[9].

You can train your own AI model with these steps:

Start by gathering and labeling plant images that show healthy and stressed conditions. Data augmentation helps create more varied training images ^[14]. Next, pull out features using methods like Gray Level Co-occurrence Matrix (GLCM) textures that capture key visual details ^[5].

AI beginners should try Support Vector Machine (SVM) algorithms instead of complex deep learning models. SVMs can sort plants into healthy or unhealthy categories based on their features ^[5]. More ambitious Raspberry Pi 5 projects can use pre-trained models like MobileNetV2, which hits 95.4% accuracy for maize without much training ^[9].

Displaying results on a dashboard

The visual dashboard makes Raspberry Pi projects exciting as you watch your plants’ health in real time. A Grow HAT Mini works great with its small screen and buttons for easy navigation ^[11]. It comes with a piezo buzzer that alerts you about plant needs and a light sensor that prevents nighttime notifications ^[11].

Advanced coders can use cloud platforms like ThingSpeak to store and show sensor data in field charts ^[5]. This lets you check on your plants from anywhere, making it perfect for busy plant owners.

The dashboard shows everything from moisture levels to complex NDVI calculations of plant health. A complete dashboard includes:

1. Current and historical moisture readings
2. Temperature and humidity trends
3. Light exposure patterns
4. NDVI health scores with color-coded indicators (green for healthy, red for stressed) ^[10]

Computer vision algorithms can track plant growth by measuring height changes over time ^[15]. This data helps optimize care routines and compare different growing methods. The dashboard brings all this information together in an easy-to-understand format.

Retro Gaming Console with Raspberry Pi 5

Your Raspberry Pi 5 can become a retro gaming console that gives you a wealth of classic gaming experiences from multiple decades. The Pi 5’s improved specs let you copy systems from the Atari 2600 to demanding consoles like Nintendo Wii and PlayStation 3. This makes it one of the most versatile raspberry pi projects gaming enthusiasts can try.

Setting up emulators

You’ll need to pick the right emulation platform to start your retro gaming system. Here are some excellent options with their own advantages:

Batocera is maybe even the best choice you can make for Raspberry Pi 5. It gives you plug-and-play simplicity and great Bluetooth controller support. You’ll get built-in Kodi media center integration and Moonlight game streaming capabilities. The setup is simple – download the right image, flash it to your microSD card using Raspberry Pi Imager or Balena Etcher, and you’re good to go.

RetroPie remains the most popular platform with the biggest community support. Notwithstanding that, you’ll need more manual setup on Pi 5 since there’s no official image yet for this model. The original setup needs you to compile RetroPie using terminal commands—this can take several hours even with the 8GB RAM model.

Recalbox comes with an appealing easy-to-use interface. It also has Kodi pre-installed and supports LAN file transfers to make ROM management easier. The first boot takes longer than other options but gives you an excellent experience afterward.

Lakka gives you a minimalist interface based on RetroArch, so you won’t need to organize ROMs into separate directories. It uses the Japanese controller layout by default (where B/O buttons work as A/X), but you can remap this.

A microSD card of at least 32GB (64GB+ recommended) with Class 10 speed rating or better will give you the best performance. You might also want to add a small SSD or USB 3.0 flash drive to store your ROM collection.

Customizing the interface

The interface customization improves both looks and usability after you install your emulation platform. EmulationStation serves as the frontend for most platforms and supports various themes that change your system’s look and feel.

RetroPie lets you access the configuration menu by pressing Start and selecting «UI Settings» to change themes, transitions, and sounds. You can set up custom collections to organize favorite games across different systems.

Batocera and Recalbox come with built-in theme options that update regularly. They also give you web interfaces you can access from any computer on your network. This lets you manage games and settings remotely without stopping gameplay.

Your ROM files should go into system-specific folders for better organization. The emulation platform will spot the console type and pick the right emulator. New ROMs usually get their game metadata and box art automatically on most platforms, though manual customization is possible for a more personal touch.

The Raspberry Pi 5 handles many systems with great performance:

• Perfect emulation: NES, SNES, Game Boy (all versions), Sega Genesis, Neo Geo, Atari systems
• Very good performance: PlayStation 1, Nintendo 64, Dreamcast, PSP
• Playable with tweaks: PlayStation 2 (select games), GameCube (limited)

Adding wireless controllers

The right controllers make a huge difference in your retro gaming experience. The Raspberry Pi 5 works well with most USB and Bluetooth controllers you can buy today.

8BitDo controllers are great wireless options with excellent retro-styled designs and modern features. The 8BitDo Pro wired controller has a comfortable SNES-inspired layout that works great for most classic games. The 8BitDo Pro 2 gives you wireless freedom and app control with extra buttons, but costs twice as much.

Xbox and PlayStation controllers work exceptionally well too. You can connect them two ways:

1. Direct Bluetooth connection (needs initial pairing)
2. Through a wireless adapter like the 8BitDo Wireless Controller Adapter

Your emulation platform will ask you to set up your controller by mapping buttons on first boot. This creates a profile that works across all emulated systems. You can also set up system-specific controller mappings if certain games need different button layouts.

Most platforms support up to 4 controllers at once via USB for multiplayer games. Recalbox and Batocera can handle up to 8-10 players with the right setup if you use USB hubs.

A retro gaming console ranks among the coolest raspberry pi projects you can build. You’ll keep enjoying it long after you finish setting it up, whether you’re playing childhood favorites or trying classics for the first time.

Invisible Display Using Pepper’s Ghost Effect

A transparent display using the Pepper’s Ghost effect ranks among the most fascinating Raspberry Pi projects you can build. This Victorian-era optical illusion creates floating, transparent images that appear and vanish like magic. Your 19th-century parlor trick becomes an impressive interactive display that engages everyone who sees it when paired with a Raspberry Pi.

What is the Pepper’s Ghost illusion?

John Henry Pepper made this illusion famous in the 1860s during theatrical performances. The effect produces a ghostly image by reflecting objects off a glass sheet positioned at a 45-degree angle. This clever optical trick makes objects look like they float in mid-air or materialize slowly.

The science works in a straightforward way. Light hitting a semi-reflective surface at an angle splits – some passes through while some reflects. You can make reflections appear and disappear by controlling the lighting on both sides of the glass. Our brains can’t easily tell the difference between the actual object and its reflection when done right.

Modern Raspberry Pi projects have taken this Victorian illusion to new heights. They use current materials and digital displays to create amazing interactive experiences without expensive holographic technology.

How to build the transparent screen

You’ll need some planning to build your own Pepper’s Ghost display. The materials are relatively affordable:

1. Materials needed:
   • Raspberry Pi (3B+ or newer recommended)
   • LCD monitor (higher brightness works better)
   • Thin acrylic or glass sheet
   • Black fabric/cardboard for backdrop
   • Wooden frame materials
   • HDMI cable and power supply
2. Construction process:
   Start by building a wooden frame that positions your acrylic sheet at exactly 45 degrees between the viewer and the hidden display. Mount the display horizontally facing upward toward the acrylic. Black material should cover all areas around and behind the display to stop unwanted reflections.
3. Software setup:
   Your Raspberry Pi must display content upside-down since the reflection will invert it. Add this to your config.txt file:

   display_rotate=180
   

   Dark backgrounds with bright elements create the best results. Dark areas appear transparent while bright elements float in space.

This project stands out among beginner Raspberry Pi projects because even simple animations look impressive. Motion sensors can trigger content only when someone approaches, which boosts both power efficiency and surprise factor.

Best use cases for this project

The Pepper’s Ghost effect shines in several applications:

• Museum exhibits: Historical figures materialize and speak directly to visitors
• Halloween decorations: Animated ghosts float in doorways or windows
• Retail displays: Products appear with floating text highlighting features
• Board game enhancements: Digital elements blend with physical games
• Conference presentations: Objects float during demonstrations

These techniques are the foundations for many commercial «holographic» displays at trade shows and concerts. Scaling up with multiple Raspberry Pi units controlling synchronized displays creates immersive spaces where digital content exists in the physical world.

The illusion works best in controlled lighting conditions. Indoor installations prove ideal for Raspberry Pi projects of this type since direct sunlight washes out the effect. A well-executed invisible display creates wonder that regular screens just can’t match.

Raspberry Pi-Powered Cat House Automation

Building a cozy hideaway for your cats is one of the most rewarding Raspberry Pi projects you can tackle. Your Raspberry Pi can turn a basic cat house into a smart home that keeps your pets comfortable all year round. Smart sensor placement and the right code will make this possible whatever the weather outside.

Temperature and humidity control

A good climate control system sits at the core of any automated cat house. You can build a smart system with a Raspberry Pi and the right sensors to maintain a comfortable 70°F inside the cat house even when outdoor temperatures drop to -27°F ^[16]. The system uses heating elements under the floor to create a warm, cozy surface where cats love to rest.

The setup needs a temperature sensor connected to your Pi through the 1-wire protocol. The process is simple – just add «dtoverlay=w1-gpio» to your boot configuration file ^[17]. Your Python script can then control the heating elements when temperatures fall below 72°F for optimal feline comfort ^[17].

The system works best with both temperature and humidity sensors to stop dampness and mold growth ^[7]. This setup will give your cat house proper warmth and ventilation. This feature helps kittens, older cats, and pets with health issues who react more to their environment.

Motion detection and camera feed

Smart cat houses become even better when you know exactly when your pets come and go. Motion sensors can trigger many automated actions, from heat activation to recording your pet’s activities ^[16].

You can watch your pets any time with night vision cameras ^[16]. The camera feed streams straight to your local network devices with basic tools like VLC player ^[17]. You can add thermal vision layers to regular video for better monitoring ^[8].

Setting up the video stream takes just a few commands:

raspivid -o - -t 0 -hf -w 640 -h 360 -fps 25 | cvlc -vvv stream:///dev/stdin –sout '#rtp{sdp=rtsp://:8554}' :demux=h264

This creates a video feed you can access through RTSP protocol from any network device ^[17].

Feeding system integration

Automated feeding stands out as the most practical part of Raspberry Pi pet care coding. Servo motors connected to regular dry food dispensers create systems you can trigger even through email commands ^[18]. This feature helps a lot when your schedule changes unexpectedly.

IFTTT integration handles regular feeding times without manual input ^[18]. Advanced setups use weight scales to measure food portions accurately ^[19]. The system sends email alerts when food runs low ^[19], so you never worry about empty feeders.

These three elements – climate control, monitoring, and feeding – work together to create a detailed care system. Your cats stay comfortable, safe, and well-fed even when you’re away.

Real-Time Subway Map with Fiber Optics

This raspberry pi project brings data visualization and physical art together in an amazing way. You can build a beautiful 3D map that shows subway train locations across a city network by combining fiber optics with immediate transit data.

How the data is fetched

The General Transit Feed Specification (GTFS) Realtime sits at the heart of this project. This feed specification lets transportation agencies give current information about their fleet ^[20]. The Metropolitan Transportation Authority (MTA) runs a free, open server that anyone can use to get real-time train data in a standardized format ^[1].

Your Raspberry Pi grabs this transit information every 30 seconds ^[1]. This timing works well with most transit authorities’ data server updates. While faster updates could work, the transit data rarely changes more often than this.

The feed gives you key real-time details like:

• Trip updates (delays, cancelations, route changes)
• Service alerts (moved stops, unforeseen events)
• Vehicle positions (including location and congestion level)

Protocol Buffers handles the data exchange—a language-neutral way to serialize structured data that beats XML in size and speed ^[20]. Your Raspberry Pi can decode train positions reliably through this standardized method without maxing out its processor.

Building the 3D map

The physical map starts as a 2D drawing. Software like OpenSCAD turns this into 3D-printable models ^[4]. The printed result becomes your display’s visible surface.

The real magic happens behind this surface. Optical fibers connect each map position to LED matrices underneath ^[6]. These fiber optic lines trace the actual subway routes and create a clear visual guide. The setup works just like commercial fiber optic displays, sending light from one source to exact spots on your map.

Many builders choose fiber optic strands with small «bubbles» to make the whole length glow instead of just the ends ^[21]. Light that leaks from the fiber sides creates cool color effects that make the display pop ^[22].

Controlling LEDs with Raspberry Pi

The light comes from one or two 8×32 RGB LED matrices hidden under the map ^[4]. Your Raspberry Pi drives these matrices and maps the LED grid to subway track positions.

You only need a few things to connect your Raspberry Pi to the LEDs:

• Connect the Pi’s ground pin to the LED matrix ground
• Connect 5V to the LED power
• Connect a GPIO pin (often GP15) to the data input pin

The code uses an array to match each LED to its display position ^[22]. This turns the regular LED grid into a pattern matching subway stations and tracks. Each optical fiber carries light from its LED to the right spot on the map.

This project shows why Raspberry Pi works so well for creative visualization. It mixes simple computing with physical beauty ^[1].

AI Pizza Clock That Tells Time with Images

Time-telling becomes a delicious affair through this imaginative raspberry pi project. Ever wondered what time it is in pizza slices? This quirky creation transforms a traditional clock into an AI-generated food display that works perfectly and looks appetizing.

Concept and design

The basic contours of the AI Pizza Clock are simple – a virtual pizza pan fills up with slices as morning moves toward noon, then empties until midnight before the cycle starts again ^[2]. You don’t watch hands move around a dial. Instead, you see a pizza being made and eaten throughout the day.

A Raspberry Pi Zero W powers everything with minimal energy consumption in this remarkably simple hardware setup. A compact 4-inch diameter LCD connected through an HDMI adapter displays the output ^[2]. These components fit perfectly inside a custom-designed case built with SolidPython and OpenSCAD ^[3].

Using AI to generate images

The clock runs a sophisticated two-stage algorithm based on Stable Diffusion 1.5 to create its mouthwatering displays ^[2]. The system creates a template that shows the pizza’s size and shape based on the current time ^[3]. This template then goes through the AI model to generate a realistic-looking pizza overlay.

The results turn out charmingly imperfect with «suspiciously uncooked whole basil sprigs along with weird pepperoni slices and Dali-esque globs of cheese» ^[2]. These quirky flaws give each passing hour its unique character.

Customizing with your own themes

Pizza isn’t your favorite food? The system lets you go beyond tomato sauce and cheese. Users can add any circular image instead of pizza ^[3]. Creative alternatives include flower designs that bloom through the day or clock faces filled with color.

A web app version lets you enjoy this unique timekeeping experience on your desktop if you don’t want to build physical hardware ^[2]. Note that Stable Diffusion works with countless themes, making this one of the most customizable raspberry pi projects creative coders can build.

Dual Raspberry Pi Pico Mini PC

Two Raspberry Pi Picos working together can redefine the limits of what these tiny devices achieve. This clever pairing turns simple microcontrollers into a capable mini PC system. The results are quite versatile.

Why use two Picos?

Task distribution makes dual Pico setups brilliant. One Pico works as a dedicated GPU that handles visual processing tasks, while the other serves as the main processor in many setups ^[23]. Each core reaches 100% CPU utilization without any interference from its partner ^[24].

These Picos are different from standard Raspberry Pi computers. They boot right away without any shutdown procedures—you just turn them on and they work ^[25]. The power consumption stays nowhere near their larger counterparts, yet they pack impressive capabilities with dual-core Cortex-M0+ processors running at up to 133 MHz ^[11].

The hardware FIFO makes shared data exchange efficient without kernel drivers, arbitration, or complex timing issues ^[24]. This creates a user-friendly programming environment where cores can focus on their assigned tasks.

Designing the case

Dual Pico projects need a well-planned enclosure. Most makers employ 3D printing with models from Fusion 360 or OpenSCAD ^[26]. Their designs include button cutouts, side groves, and specific openings for wires from GPIO pins ^[26].

The Pico’s connection interface gives you two mounting choices. You get castellated connection points for surface-mount soldering and through-hole vias for standard headers ^[27]. This setup works great for both temporary development connections and permanent installation.

Performance and limitations

Dual Pico systems come with some constraints. The biggest problem is wireless connectivity—Picos don’t have built-in WiFi or Bluetooth, so they need external components for wireless communication ^[25].

Memory is another key factor with 264KB of onboard SRAM ^[28]. The 2MB of flash memory helps offset this limit, and there’s support for up to 16MB of off-chip flash through the dedicated QSPI bus ^[27].

Picos shine in specialized applications with features you won’t find in larger Raspberry Pi models. Their four analog input pins provide on-board analog-to-digital conversion ^[25].

Conclusion

My exploration of hidden Raspberry Pi projects revealed amazing ways makers challenge what these tiny computers can do. Smart mirrors show your daily schedule while AI systems track plant health. The versatility of Raspberry Pi amazes me. Projects like the retro gaming console and Pepper’s Ghost display show how advanced technology can turn nostalgic concepts into modern tools.

These projects prove more than technical capabilities – they solve real-life challenges. The automated cat house keeps pets comfortable whatever the weather. A fiber optic subway map transforms raw data into physical art. The AI pizza clock and dual Pico mini PC show how creativity runs on hardware limits rather than fighting them.

The balance between complexity and availability stands out in these Raspberry Pi projects. Simple components deliver impressive results. On top of that, users can adapt most projects to match their priorities. Smart mirror modules adjust easily and the AI clock theme switches from pizza to flowers.

This spirit of experimentation and knowledge-sharing powers the Raspberry Pi community. Builders worldwide find new ways to use these flexible boards. Hardware hacking, AI implementation, and creative interfaces offer something to get you started in thinking about your next project.

These eight hidden projects should help you see Raspberry Pi beyond its basic uses. Magic happens when existing ideas blend with your creativity. Your weekend project could inspire someone else’s next creation. This wonderful cycle of innovation makes the Raspberry Pi community truly special.

FAQs

Q1. What are some unique Raspberry Pi projects beyond basic coding?
Raspberry Pi can be used for a wide range of innovative projects, including creating smart mirrors with voice assistants, building AI-powered plant health monitors, designing retro gaming consoles, and even developing invisible displays using optical illusions like the Pepper’s Ghost effect.

Q2. Can a Raspberry Pi be used to automate a pet’s living space?
Yes, Raspberry Pi can be used to create an automated smart house for pets, particularly cats. Features can include temperature and humidity control, motion detection with camera feeds, and even automated feeding systems. This allows pet owners to maintain ideal conditions and monitor their pets remotely.

Q3. How can Raspberry Pi be used for creative data visualization?
One creative example is using Raspberry Pi to build a real-time subway map with fiber optics. This project combines live transit data with physical LEDs and fiber optic strands to create a dynamic, illuminated map that shows train positions in real-time.

Q4. Is it possible to create unconventional timekeeping devices with Raspberry Pi?
Absolutely. An example is the AI Pizza Clock, which uses artificial intelligence to generate images of pizzas that represent the current time. As the day progresses, the virtual pizza is «assembled» and then «consumed,» offering a unique and appetizing way to tell time.

Q5. What advantages does using multiple Raspberry Pi Picos offer?
Using two Raspberry Pi Picos together can create a mini PC with enhanced capabilities. One Pico can act as a dedicated GPU for visual processing, while the other serves as the main processor. This setup allows for efficient task distribution and can achieve 100% CPU utilization on each core without interference.

References

[1] – https://www.xda-developers.com/3d-live-map-manhattan-subway-trains-raspberry-pi/
[2] – https://hackaday.com/2025/02/11/its-always-pizza-oclock-with-this-ai-powered-timepiece/
[3] – https://www.tomshardware.com/raspberry-pi/this-raspberry-pi-ai-pizza-clock-tells-the-time-one-slice-at-a-time
[4] – https://www.hackster.io/news/this-3d-printed-map-of-manhattan-displays-subway-train-locations-in-real-time-via-a-raspberry-pi-2c21dbc4296f
[5] – https://www.researchgate.net/publication/350989817_Automated_machine_learning_based_plant_stress_detection_system
[6] – https://blog.adafruit.com/2025/02/19/a-raspberry-pi-map-of-manhattan-which-shows-subway-train-status/
[7] – https://www.backyardpetsupplies.com/product-category/kennel-parts/kennel-climate-control?srsltid=AfmBOoqhcU4yGwBd81bKnu0pypbOcS5qlgaj7KezCNrwdhASMAGzmGQn
[8] – https://www.reddit.com/r/raspberry_pi/comments/1j1tzwr/i_made_a_smart_talking_winter_cat_shelter_with/
[9] – https://www.sciencedirect.com/science/article/abs/pii/S0952197624000216
[10] – https://hackaday.io/project/191333-plant-foliage-health-monitor
[11] – https://community.element14.com/products/roadtest/rv/roadtest_reviews/964/raspberry_pi_pico
[12] – https://linuxgizmos.com/raspberry-pi-based-garden-monitoring-system-supplies-five-sensors/
[13] – https://www.postscapes.com/smart-greenhouse-sensors-and-cameras/
[14] – https://www.sciencedirect.com/science/article/pii/S0168169924011256
[15] – https://www.sciencedirect.com/science/article/pii/S2772375524000546
[16] – https://www.tomshardware.com/raspberry-pi/cozy-cats-live-in-a-raspberry-pi-powered-luxury-automated-smart-house
[17] – https://www.instructables.com/Smart-Enough-Outdoor-Cat-House/
[18] – https://www.pibeginners.com/raspberry-pi-pet-care-automation/
[19] – https://www.storiknow.com/automatic-cat-feeder-using-raspberry-pi/
[20] – https://developers.google.com/transit/gtfs-realtime
[21] – https://forums.raspberrypi.com/viewtopic.php?t=59617
[22] – https://www.raspberrypi.com/news/fiber-optic-pico-matrix-display/
[23] – https://www.tomshardware.com/raspberry-pi/dual-raspberry-pi-picos-power-this-portable-mini-pc
[24] – https://forums.raspberrypi.com/viewtopic.php?t=324763
[25] – https://www.tomshardware.com/reviews/raspberry-pi-pico-review
[26] – https://www.instructables.com/Maker-Pi-Pico-Travel-Case/
[27] – https://community.element14.com/products/roadtest/rv/roadtest_reviews/967/raspberry_pi_pico_1
[28] – https://magpi.raspberrypi.com/articles/raspberry-pi-pico-microcontroller-specifications-features-and-rp2040