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#smart-home — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #smart-home, aggregated by home.social.

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  1. Cover your whole property with 4 solar-powered 2K cameras. Color night vision, spotlight, no cables.

    ANRAN Solar Security Cameras Wireless Outdoor Built-in Solar Panel

    🔭 https://www.amazon.com/dp/B0D1TSH73Z?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    ANRAN Solar Security Cameras W...

  2. Solar-powered security camera that never needs recharging. AI human detection + color night vision ☀️

    Noorio 1080P Solar Security Camera Wireless Outdoor

    🔭 https://www.amazon.com/dp/B0GBXM22H6?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    Noorio 1080P Solar Security Ca...

  3. The 4-camera solar security bundle that works with Alexa and never needs recharging.

    ANRAN Solar Security Cameras Wireless Outdoor Built-in Solar Panel

    🔭 https://www.amazon.com/dp/B0D1TSH73Z?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    ANRAN Solar Security Cameras W...

  4. Indoor/outdoor dome cameras with 80ft IR night vision. HD-TVI compatible, dirt cheap per cam.

    ZOSI 2Pack 2.0MP HD 1080P 1920TVL CCTV Dome Security Cameras

    🔭 https://www.amazon.com/dp/B08ZXXG9MR?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    ZOSI 2Pack 2.0MP HD 1080P 1920...

  5. ANRAN 4-pack: battery + solar powered WiFi cameras with AI detection and Alexa support.

    ANRAN Solar Security Cameras Wireless Outdoor Built-in Solar Panel

    🔭 https://www.amazon.com/dp/B0D1TSH73Z?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    ANRAN Solar Security Cameras W...

  6. 2-pack of 1080P dome cameras with 80ft night vision for DVR systems. $46 for both 🛡️

    ZOSI 2Pack 2.0MP HD 1080P 1920TVL CCTV Dome Security Cameras

    🔭 https://www.amazon.com/dp/B08ZXXG9MR?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    ZOSI 2Pack 2.0MP HD 1080P 1920...

  7. Follow-up to my Jev × Home Assistant post: two comments on the last one deserved a real answer, not just a reply.

    @oneclickclaw_io asked why not feed Jev's context to a small local model instead. Fair point - my prompts really were just snapshots (humidity *now*, flow *now*), no memory of what led there.

    @nocalla asked whether that's not exactly what the Bayesian sensor is for.

    Both got tested, not just answered:

    → Why not local: the box is an N100 mini PC, 4 cores, 16 GB RAM, no GPU, already running HA Core + recorder + Zigbee2MQTT. A local model's own numbers (from the router benchmark) put it at 1.5-3s/call on that class of hardware, several times an hour, contending with real-time Zigbee. And the actual gap was never model intelligence - Jev has a 32k-token window and was only getting ~565 tokens of *current* facts.

    → So instead: a compact-history script built on Home Assistant's own recorder statistics, a 24h house timeline, per-room humidity baselines, a broken-sensor safety net (turns out two humidity sensors had been stuck at 0% - again), per-decision shadow/active switches, and a feedback loop - "who was right?" on the phone, scored on a scoreboard, summarised every week.

    → Bayesian sensor: close, but not the same tool. You hand-estimate every probability yourself, it's strictly on/off, treats correlated clues as independent, and has no idea when its own inputs are lying. Jev takes plain facts, returns a full distribution over N options, and reasons over the whole state. Bayesian still wins for signals you already understand and want fully offline (occupancy, say) - and the two combine nicely.

    Real production numbers from the first days: 267 calls, ~206k tokens, $0.0087 that day. And a live finding I didn't expect: the VMC decision disagrees with its own rule 14/14 times at low confidence, while the shutters decision agrees 78/78 times - exactly why the per-decision switch earns its keep.

    Full write-up:
    blog.mornati.net/jev-home-assi

    #HomeAssistant #SmartHome #HomeAutomation #AI #LLM #SelfHosted

  8. Follow-up to my Jev × Home Assistant post: two comments on the last one deserved a real answer, not just a reply.

    @oneclickclaw_io asked why not feed Jev's context to a small local model instead. Fair point - my prompts really were just snapshots (humidity *now*, flow *now*), no memory of what led there.

    @nocalla asked whether that's not exactly what the Bayesian sensor is for.

    Both got tested, not just answered:

    → Why not local: the box is an N100 mini PC, 4 cores, 16 GB RAM, no GPU, already running HA Core + recorder + Zigbee2MQTT. A local model's own numbers (from the router benchmark) put it at 1.5-3s/call on that class of hardware, several times an hour, contending with real-time Zigbee. And the actual gap was never model intelligence - Jev has a 32k-token window and was only getting ~565 tokens of *current* facts.

    → So instead: a compact-history script built on Home Assistant's own recorder statistics, a 24h house timeline, per-room humidity baselines, a broken-sensor safety net (turns out two humidity sensors had been stuck at 0% - again), per-decision shadow/active switches, and a feedback loop - "who was right?" on the phone, scored on a scoreboard, summarised every week.

    → Bayesian sensor: close, but not the same tool. You hand-estimate every probability yourself, it's strictly on/off, treats correlated clues as independent, and has no idea when its own inputs are lying. Jev takes plain facts, returns a full distribution over N options, and reasons over the whole state. Bayesian still wins for signals you already understand and want fully offline (occupancy, say) - and the two combine nicely.

    Real production numbers from the first days: 267 calls, ~206k tokens, $0.0087 that day. And a live finding I didn't expect: the VMC decision disagrees with its own rule 14/14 times at low confidence, while the shutters decision agrees 78/78 times - exactly why the per-decision switch earns its keep.

    Full write-up:
    blog.mornati.net/jev-home-assi

    #HomeAssistant #SmartHome #HomeAutomation #AI #LLM #SelfHosted

  9. Follow-up to my Jev × Home Assistant post: two comments on the last one deserved a real answer, not just a reply.

    @oneclickclaw_io asked why not feed Jev's context to a small local model instead. Fair point - my prompts really were just snapshots (humidity *now*, flow *now*), no memory of what led there.

    @nocalla asked whether that's not exactly what the Bayesian sensor is for.

    Both got tested, not just answered:

    → Why not local: the box is an N100 mini PC, 4 cores, 16 GB RAM, no GPU, already running HA Core + recorder + Zigbee2MQTT. A local model's own numbers (from the router benchmark) put it at 1.5-3s/call on that class of hardware, several times an hour, contending with real-time Zigbee. And the actual gap was never model intelligence - Jev has a 32k-token window and was only getting ~565 tokens of *current* facts.

    → So instead: a compact-history script built on Home Assistant's own recorder statistics, a 24h house timeline, per-room humidity baselines, a broken-sensor safety net (turns out two humidity sensors had been stuck at 0% - again), per-decision shadow/active switches, and a feedback loop - "who was right?" on the phone, scored on a scoreboard, summarised every week.

    → Bayesian sensor: close, but not the same tool. You hand-estimate every probability yourself, it's strictly on/off, treats correlated clues as independent, and has no idea when its own inputs are lying. Jev takes plain facts, returns a full distribution over N options, and reasons over the whole state. Bayesian still wins for signals you already understand and want fully offline (occupancy, say) - and the two combine nicely.

    Real production numbers from the first days: 267 calls, ~206k tokens, $0.0087 that day. And a live finding I didn't expect: the VMC decision disagrees with its own rule 14/14 times at low confidence, while the shutters decision agrees 78/78 times - exactly why the per-decision switch earns its keep.

    Full write-up:
    blog.mornati.net/jev-home-assi

  10. Dimmable LED candelabra bulbs — vintage warm light with modern efficiency. 6-pack, $24 💡

    AMDTU E12 LED Candelabra Light Bulb 25W Frosted Chandelier Dimmable

    🔭 https://www.amazon.com/dp/B0BW2XK2T7?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    AMDTU E12 LED Candelabra Light...

  11. Solar + battery + AI detection + color night vision — the complete wireless security setup, under $60.

    Noorio 1080P Solar Security Camera Wireless Outdoor

    🔭 https://www.amazon.com/dp/B0GBXM22H6?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    Noorio 1080P Solar Security Ca...

  12. 5G + 2.4G WiFi solar camera with expandable local storage. $56 and it protects your whole property.

    Noorio 1080P Solar Security Camera Wireless Outdoor

    🔭 https://www.amazon.com/dp/B0GBXM22H6?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    Noorio 1080P Solar Security Ca...

  13. Give your dining room warm, efficient light — this 6-pack of dimmable LED candles is it.

    AMDTU E12 LED Candelabra Light Bulb 25W Frosted Chandelier Dimmable

    🔭 https://www.amazon.com/dp/B0BW2XK2T7?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    AMDTU E12 LED Candelabra Light...

  14. 6 vintage-style E12 LED bulbs that slash energy use while keeping cozy warm light.

    AMDTU E12 LED Candelabra Light Bulb 25W Frosted Chandelier Dimmable

    🔭 https://www.amazon.com/dp/B0BW2XK2T7?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    AMDTU E12 LED Candelabra Light...

  15. 1080P solar security camera with AI human detection. No monthly fees, free local storage.

    Noorio 1080P Solar Security Camera Wireless Outdoor

    🔭 https://www.amazon.com/dp/B0GBXM22H6?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    Noorio 1080P Solar Security Ca...

  16. Wireless 2K solar cameras with color night vision. 4 cameras, one property, zero wiring.

    ANRAN Solar Security Cameras Wireless Outdoor Built-in Solar Panel

    🔭 https://www.amazon.com/dp/B0D1TSH73Z?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    ANRAN Solar Security Cameras W...

  17. 1TB of local storage, 4 wired cameras, AI detection. The surveillance system without subscriptions.

    5MP WiFi Home Security Camera System Outdoor

    🔭 https://www.amazon.com/dp/B0GJ5KWVR3?tag=jwebb004-20 #ad #paidlink #AmazonAffiliate #SmartHome #HomeSecurity

    5MP WiFi Home Security Camera ...

  18. Analoge Strommessdosen und Raumklimageräte anschaffen oder Zigbee/Matter-kompatible Geräte holen und in Home Assistant einsteigen?

    Ich möchte wissen, wie viel Strom durch welche Steckdose geht und welche Temperatur und Luftfeuchtigkeit in welchem Raum zu welcher Zeit bestehen.

    Das alles digital und vernetzt zu haben, vielleicht sogar in Grafana ein Dashboard dazu bauen zu können, klingt schon praktisch

    #smarthome #homeAssistant #internetOfThings #energiekostenmessgerät #heizen #strom #zigbee #matter

  19. Analoge Strommessdosen und Raumklimageräte anschaffen oder Zigbee/Matter-kompatible Geräte holen und in Home Assistant einsteigen?

    Ich möchte wissen, wie viel Strom durch welche Steckdose geht und welche Temperatur und Luftfeuchtigkeit in welchem Raum zu welcher Zeit bestehen.

    Das alles digital und vernetzt zu haben, vielleicht sogar in Grafana ein Dashboard dazu bauen zu können, klingt schon praktisch

    #smarthome #homeAssistant #internetOfThings #energiekostenmessgerät #heizen #strom #zigbee #matter

  20. Heating accounts for 80% of energy use in EU homes, making it our largest winter expense. Managing this cost is critical for many.

    We explain how to strategically use technology to stop waste based on your budget, covering everything from under-€30 diagnostics to smart home upgrades and dynamic tariffs.

    movetheneedle.news/brands/mtn-

    #energy #efficiency #smarthome #sustainability #Europe #EU #technology #energypoverty #innovation

  21. Heating accounts for 80% of energy use in EU homes, making it our largest winter expense. Managing this cost is critical for many.

    We explain how to strategically use technology to stop waste based on your budget, covering everything from under-€30 diagnostics to smart home upgrades and dynamic tariffs.

    movetheneedle.news/brands/mtn-

    #energy #efficiency #smarthome #sustainability #Europe #EU #technology #energypoverty #innovation

  22. My home automations know thresholds, not context.

    Sump pump runs 2 min after a rainy night → alert.
    Long shower → "possible leak".
    Washer pauses to soak → "finished", 20 min too early.

    So I gave the "is this normal?" question to Jev, TypeSafe's decision model. You send it a few lines of facts and a typed question, and it answers with a calibrated probability. No free text, no JSON to parse.

    How it's wired into Home Assistant:
    • The old rule always computes its answer. Jev only advises.
    • One switch: shadow (log only), active, or off.
    • An error, a spent budget or low confidence → the rule wins, so the alert still fires.
    • 6 automations: sump pump, water, temperature drops, shutters, ventilation, laundry.

    Cost: 133 calls and 75k tokens on day one, about $3 a year for the whole house.

    Two lessons that aren't about AI:
    1. Writing the facts for the model made me read them. Two humidity sensors had been stuck at 0 %, and my old rules were using them.
    2. My GitOps sync had been failing silently for 5 weeks. Merged ≠ deployed.

    Also in the post: can Laya do the same job locally, to keep occupancy data at home?

    blog.mornati.net/jev-home-assi

    #HomeAssistant #SmartHome #HomeAutomation #LLM #AI #SelfHosted

  23. My home automations know thresholds, not context.

    Sump pump runs 2 min after a rainy night → alert.
    Long shower → "possible leak".
    Washer pauses to soak → "finished", 20 min too early.

    So I gave the "is this normal?" question to Jev, TypeSafe's decision model. You send it a few lines of facts and a typed question, and it answers with a calibrated probability. No free text, no JSON to parse.

    How it's wired into Home Assistant:
    • The old rule always computes its answer. Jev only advises.
    • One switch: shadow (log only), active, or off.
    • An error, a spent budget or low confidence → the rule wins, so the alert still fires.
    • 6 automations: sump pump, water, temperature drops, shutters, ventilation, laundry.

    Cost: 133 calls and 75k tokens on day one, about $3 a year for the whole house.

    Two lessons that aren't about AI:
    1. Writing the facts for the model made me read them. Two humidity sensors had been stuck at 0 %, and my old rules were using them.
    2. My GitOps sync had been failing silently for 5 weeks. Merged ≠ deployed.

    Also in the post: can Laya do the same job locally, to keep occupancy data at home?

    blog.mornati.net/jev-home-assi

  24. Es gibt Dinge im #SmartHome , die sind nüchtern betrachtet irgendwo zwischen sinnlos und ähhh....

    Aber wenn ich noch im Supermarkt den Backofen auf die korrekte Temperatur vorheize, meine Wohnungstür automatisch aufgeht, wenn ich nach Hause und ich direkt die Pizza in den Ofen schieben kann, dann ist das schon ein bisschen wie Magie 🙃

  25. Es gibt Dinge im #SmartHome , die sind nüchtern betrachtet irgendwo zwischen sinnlos und ähhh....

    Aber wenn ich noch im Supermarkt den Backofen auf die korrekte Temperatur vorheize, meine Wohnungstür automatisch aufgeht, wenn ich nach Hause und ich direkt die Pizza in den Ofen schieben kann, dann ist das schon ein bisschen wie Magie 🙃

  26. heise+ | BodyFit vs. BodyScan 2: Welche Withings-Waage sich lohnt

    Withings will mit BodyFit und BodyScan 2 weit mehr als Gewicht messen. Der Test zeigt, für wen die teuren Analysewaagen eine sinnvolle Investition sind.

    heise.de/tests/BodyFit-vs-Body

    #FitnessTracker #Gesundheit #Journal #SmartHome #Test #Wearables #news

  27. heise+ | BodyFit vs. BodyScan 2: Welche Withings-Waage sich lohnt

    Withings will mit BodyFit und BodyScan 2 weit mehr als Gewicht messen. Der Test zeigt, für wen die teuren Analysewaagen eine sinnvolle Investition sind.

    heise.de/tests/BodyFit-vs-Body

    #FitnessTracker #Gesundheit #Journal #SmartHome #Test #Wearables #news

  28. Your smart devices map your daily routine, but many connected gadgets gather far more data than they need. What are they tracking behind the scenes? Does your air fryer really need to know anything about you to make the chips?

    We provide practical steps you can take today to protect your privacy and secure your connected home.

    movetheneedle.news/brands/mtn-

    #AI #technology #smarthome #innovation #IoT #dataprotection #privacy #tech

  29. Your smart devices map your daily routine, but many connected gadgets gather far more data than they need. What are they tracking behind the scenes? Does your air fryer really need to know anything about you to make the chips?

    We provide practical steps you can take today to protect your privacy and secure your connected home.

    movetheneedle.news/brands/mtn-

    #AI #technology #smarthome #innovation #IoT #dataprotection #privacy #tech

  30. A few years back, I was at a beachside Easter egg hunt, watching my kids dash through sand dunes searching for sweet treats. My phone buzzed in my pocket; I ignored it. A moment later, it buzzed again. I pulled it out, glanced down, and saw a "motion detected" notification from my security camera. "Just […]#AI #Apple #Reviews #SmartHome #SmartwatchReviews #Tech
    Apple is making your security camera smarter. What comes next is more interesting.
  31. A few years back, I was at a beachside Easter egg hunt, watching my kids dash through sand dunes searching for sweet treats. My phone buzzed in my pocket; I ignored it. A moment later, it buzzed again. I pulled it out, glanced down, and saw a "motion detected" notification from my security camera. "Just […]#AI #Apple #Reviews #SmartHome #SmartwatchReviews #Tech
    Apple is making your security camera smarter. What comes next is more interesting.
  32. Ich nutze seit dieser Woche #MusicAssistant von @homeassistant und bin mehr als begeistert.

    Diese ganzen Möglichkeiten Musik zu hören und Systeme zu verknüpfen, die sonst nicht verknüpfbar sind. 😍

    #Smarthome #homeassistant #music

  33. Ich nutze seit dieser Woche #MusicAssistant von @homeassistant und bin mehr als begeistert.

    Diese ganzen Möglichkeiten Musik zu hören und Systeme zu verknüpfen, die sonst nicht verknüpfbar sind. 😍

    #Smarthome #homeassistant #music

  34. Fact-Friday: Automatisierte Beleuchtung in deinem Smart Home kann nicht nur Energie sparen, sondern auch die Atmosphäre verändern! 💡✨ Programmiere dein Licht nach Tageszeit oder Stimmung und erlebe dein Zuhause ganz neu! #SmartHome #Lichtsteuerung #HomeAutomation

  35. Immer wieder frustriert, dass wir nur flache Dosen haben. Lust, ne neue zu Bohren habe ich eigentlich nicht.

    Andererseits mal die Frage: dieser Dimmer schaltet auf Impuls eines Präsenzsensors eine Deckenlampe.

    Brauche ich eigentlich noch einen Taster?

    Wie würdest du das machen?
    #smarthome #homeassistant #homeautomation #shelly #elektrotechnik @homeassistant

  36. Immer wieder frustriert, dass wir nur flache Dosen haben. Lust, ne neue zu Bohren habe ich eigentlich nicht.

    Andererseits mal die Frage: dieser Dimmer schaltet auf Impuls eines Präsenzsensors eine Deckenlampe.

    Brauche ich eigentlich noch einen Taster?

    Wie würdest du das machen?
    #smarthome #homeassistant #homeautomation #shelly #elektrotechnik @homeassistant

  37. I put voice control for my whole smart home on a smart ring. Double click and hold, speak, and a couple seconds later the lights turn on (or off). It works via a small open-source MCP server I run at home:

    github.com/jcrabapple/pebble-i

    The Pebble Index ring has two capture modes. Single click stays on-device. Double click and hold sends speech to Pebble's cloud service, which can call tools on your own MCP server over MCP. Mine runs as a systemd service on my desktop, exposed through a Cloudflare tunnel, bearer auth required, secrets in a 0600 env file.

    Five tools:

    - vault_search / vault_read / vault_append: search, read, and append to my Obsidian vault (path-sandboxed)
    - web_search: live search via the Exa API
    - ha_control: smart home commands straight to the Home Assistant REST API

    ha_control is the interesting one. My first version routed commands through a general-purpose assistant, which worked but took minutes. So ha_control now handles them directly: it parses the spoken phrase, token-matches it against Home Assistant's entity list, calls the service, and polls the state readback to confirm. Fully deterministic, no model in the path. Room groups beat individual fixtures, unavailable entities get skipped, ambiguous matches return the candidate list instead of guessing. "Living room lights off" gets a confirmed result in about a second.

    If you want one, you need the ring, an always-on machine, a Cloudflare tunnel or similar, and Home Assistant. Repo has the server, tests, a phone-side setup checklist, and notes on the Pebble app's less documented behavior. MIT licensed.

    #pebble #smarthome #mcp #homeassistant #selfhosted

  38. I put voice control for my whole smart home on a smart ring. Double click and hold, speak, and a couple seconds later the lights turn on (or off). It works via a small open-source MCP server I run at home:

    github.com/jcrabapple/pebble-i

    The Pebble Index ring has two capture modes. Single click stays on-device. Double click and hold sends speech to Pebble's cloud service, which can call tools on your own MCP server over MCP. Mine runs as a systemd service on my desktop, exposed through a Cloudflare tunnel, bearer auth required, secrets in a 0600 env file.

    Five tools:

    - vault_search / vault_read / vault_append: search, read, and append to my Obsidian vault (path-sandboxed)
    - web_search: live search via the Exa API
    - ha_control: smart home commands straight to the Home Assistant REST API

    ha_control is the interesting one. My first version routed commands through a general-purpose assistant, which worked but took minutes. So ha_control now handles them directly: it parses the spoken phrase, token-matches it against Home Assistant's entity list, calls the service, and polls the state readback to confirm. Fully deterministic, no model in the path. Room groups beat individual fixtures, unavailable entities get skipped, ambiguous matches return the candidate list instead of guessing. "Living room lights off" gets a confirmed result in about a second.

    If you want one, you need the ring, an always-on machine, a Cloudflare tunnel or similar, and Home Assistant. Repo has the server, tests, a phone-side setup checklist, and notes on the Pebble app's less documented behavior. MIT licensed.

    #pebble #smarthome #mcp #homeassistant #selfhosted