kalman post fix

JAlcocerT · Mar 19, 2024 · 45ffaad · 45ffaad
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diff --git a/_posts/2023-05-02-pi-vs-orange.md b/_posts/2023-05-02-pi-vs-orange.md
@@ -24,9 +24,8 @@ Migrating from Google Cloud Run to [self-hosting the Python DASH APP](https://fo
 
 Its reliability and energy efficiency make it ideal for running my self-hosted services, offering a reliable and cost-effective alternative to cloud-based solutions.
 
-* Rockchip RK3588S that features eight Arm Cortex-A76 cores running at 2.4GHz plus four 1.8GHz Cortex-A55 cores.
-    * The Rockchip SoC also features a Mali G510 MP4 graphics processor, which has open-source driver hope via the Panfrost driver stack
-    * The Orange Pi 5 utilizes a Mali-G610 GPU, providing solid graphics processing capabilities.
+* Rockchip RK3588S that features eight Arm Cores (4xCortex-A76 @ 2.4GHz plus 4x1.8GHz Cortex-A55).
+    * The Rockchip SoC also features a Mali G510 MP4 graphics processor, which has open-source driver hope via the Panfrost driver stack - providing solid graphics processing capabilities.
 
 ### Orange Pi 5 - CPU Benchmark
 

diff --git a/_posts/2023-12-11-rpi-gps-superset.md → _posts/2023-06-01-rpi-gps-superset.md b/_posts/2023-12-11-rpi-gps-superset.md → _posts/2023-06-01-rpi-gps-superset.md
@@ -1,12 +1,12 @@
 ---
 title: RPi IoT Project - GPS Data (VK-162) with Apache Superset
 author: JAlcocerT
-date: 2023-12-11 00:10:00 +0800
+date: 2024-06-01 00:10:00 +0800
 categories: [IoT & Data Analytics]
 tags: [Sensors,Python,MongoDB]
-image:
-  path: /img/superset.png
-  alt: IoT Project with Python, MongoDB, DHT11/22 sensors and Metabase.
+# image:
+#   path: /img/superset.png
+#   alt: IoT Project with Python, MongoDB, DHT11/22 sensors and Metabase.
 render_with_liquid: false
 ---
 

diff --git a/_posts/2024-01-01-kubernetes-rpi.md b/_posts/2024-01-01-kubernetes-rpi.md
@@ -4,9 +4,9 @@ author: JAlcocerT
 date: 2024-01-01 00:10:00 +0800
 categories: [IoT & Data Analytics]
 tags: [Sensors,Python,MongoDB]
-image:
-  path: /img/metabase.png
-  alt: IoT Project with Python, MongoDB, DHT11/22 sensors and Metabase.
+# image:
+#   path: /img/metabase.png
+#   alt: IoT Project with Python, MongoDB, DHT11/22 sensors and Metabase.
 render_with_liquid: false
 ---
 

diff --git a/_posts/2024-01-01-rpi-cv.md b/_posts/2024-01-01-rpi-cv.md
@@ -1,7 +1,7 @@
 ---
 title: RPi IoT Project - SimpleCV and OpenCV + Scrypted & HA
 author: JAlcocerT
-date: 2024-01-01 00:10:00 +0800
+date: 2024-12-31 00:10:00 +0800
 categories: [IoT & Data Analytics]
 tags: [Sensors,Python,MongoDB]
 image:

diff --git a/_posts/2024-01-01-rpi-llm-local.md b/_posts/2024-01-01-rpi-llm-local.md
@@ -1,7 +1,7 @@
 ---
 title: RPi IoT Project - SimpleCV and OpenCV + Scrypted & HA
 author: JAlcocerT
-date: 2024-01-01 00:10:00 +0800
+date: 2024-12-31 00:10:00 +0800
 categories: [IoT & Data Analytics]
 tags: [Sensors,Python,MongoDB]
 image:

diff --git a/_posts/2024-03-15-minipc-vs-pi.md b/_posts/2024-03-15-minipc-vs-pi.md
@@ -11,10 +11,13 @@ tags: [Self-Hosting, Docker]
 
 Some time ago I was making a [performance comparison between 2 popular ARM boards](https://jalcocert.github.io/RPi/posts/pi-vs-orange/).
 
-For benchmarking I used:
+Now, it is the time to see how they stand when compared with a similar in cost mini-PC.
 
-* https://github.com/JAlcocerT/Py_Trip_Planner/
+For benchmarking I've used:
+
+* Docker Building Image time for: <https://github.com/JAlcocerT/Py_Trip_Planner/>
 * Sysbench
+* Phoronix
 * Netdata
 
 > The Orange Pi (8gb) idles ~ and the RPi 4 (2gb) ~
@@ -28,7 +31,6 @@ For benchmarking I used:
 lscpu
 ```
 
-
 To connect via ssh I needed:
 
 ```sh
@@ -50,15 +52,15 @@ sysbench cpu --threads=4 run #https://github.com/akopytov/sysbench#general-comma
 _BMAX B4 - Sysbench Test_
 
 
-> The BMAX idles around ~9w with Lubuntu 22.4 LTS and the max I observed so far is ~
+> The BMAX idles around ~9w with Lubuntu 22.4 LTS and the max I observed so far is ~16W. Wifi/Bluetooh and an additional sata ssd included.
 
 
 ```sh
 git clone https://github.com/JAlcocerT/Py_Trip_Planner/
 docker build -t pytripplanner .
 ```
 
-It took ~45 seconds - Instead of 3600s and 1700s.
+It took ~45 seconds for the N95 - Instead of 3600s and 1700s.
 
 
 ![BMAX B4 - Docker Build Test](/img/minipc-vs-pis/buildingtest.png)
@@ -73,12 +75,18 @@ And these are the temperatures [registered by NetData](https://fossengineer.com/
 
 ### BMAX B4 vs Orange Pi 5
 
+Comparing N95 (x86) with the Rockchip RK3588S (ARM64).
+
+For Synthetic benchmarks I have used [phoronix](#how-to-benchmark-with-phoronix-test-suite):
+
 ![BMAX B4 - Temperature during Docker Build](/img/minipc-vs-pis/n95-cpu-phoronix.png)
 _Intel N95 4 cores with phoronix Open Source Benchmark_
 
 ![BMAX B4 - Temperature during Docker Build](/img/minipc-vs-pis/orangepi5-cpu-phoronix.png)
 _The Orange Pi 8 Cores is a beast_
 
+
+
 ---
 
 ## FAQ
@@ -145,7 +153,12 @@ You can see how for the python question, which answer was pretty detailed, took
 _BMAX B4 - MiniPC Performance while LLM inference_
 
 
-### How to Benchmark with Phoronix Test Suite
+### How to Benchmark?
+
+* Using Sysbench
+* [Monitor with Netdata](https://fossengineer.com/selfhosting-netdata/)
+
+#### with Phoronix Test Suite
 
 We can have an idea by being part of [openbenchmarking](https://openbenchmarking.org/) by using the [F/OSS Phoronix Test Suite](https://github.com/phoronix-test-suite/phoronix-test-suite/releases)
 

diff --git a/_posts/2024-01-01-MLOps.md → _posts/2024-12-30-MLOps.md b/_posts/2024-01-01-MLOps.md → _posts/2024-12-30-MLOps.md
@@ -1,12 +1,12 @@
 ---
 title: Machine Learning Ops with SBCs
 author: JAlcocerT
-date: 2024-01-01 00:10:00 +0800
+date: 2024-12-31 00:10:00 +0800
 categories: [IoT & Data Analytics]
 tags: [Sensors,Python,MongoDB]
-image:
-  path: /img/metabase.png
-  alt: IoT Project with Python, MongoDB, DHT11/22 sensors and Metabase.
+# image:
+#   path: /img/metabase.png
+#   alt: IoT Project with Python, MongoDB, DHT11/22 sensors and Metabase.
 render_with_liquid: false
 ---