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The programming languages used to build the web often find their way into apps, too. That’s largely due to software that allows developers to “reuse” the code they write for the web in products they build to run on operating systems like Linux, Android, Windows, and macOS.

See the full article here

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You can now package and deploy AWS Lambda functions as a container image of up to 10 GB.

This makes it easy to build Lambda based applications using familiar container tooling, workflows, and dependencies. Just like functions packaged as ZIP archives, functions deployed as container images will benefit from AWS Lambda’s operational simplicity, automatic scaling with sub-second startup times, high availability, and native integrations with 140 AWS services.

More information here

IoT

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IBM will begin sunsetting IBM Watson™ Personality Insights on 1 December 2020. For a period of one year from this date, you will still be able to use Personality Insights. However, as of 1 December 2021, the offering will no longer be available.

As an alternative, we encourage you to consider migrating to IBM Watson™ Natural Language Understanding, a service on IBM Cloud that uses deep learning to extract data and insights from text such as keywords, categories, sentiment, emotion, and syntax to provide insights for your business or industry.

More information on this link

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With new version of macOS released which is macOS Big Sur 11.0.x, the latest version of our VCP driver for Macintosh OSX (v5.3.5) now becomes incompatible.

The reason for this is because of new driver model change on macOS which you can find more information from links below:

https://developer.apple.com/documentation/macos-release-notes/macos-big-sur-11_0_1-release-notes
https://developer.apple.com/support/kernel-extensions/

We currently are working to update our driver to fix this issue, although due to testing requirements, we do not expect the new version of driver to be available on our website for now. So please be up to date on our page for VCP drivers below for latest information regarding to the release of the updated VCP driver for macOS Big Sur 11.0.x:

https://www.silabs.com/products/development-tools/software/usb-to-uart-bridge-vcp-drivers

My upgrade to Big Sur will not be possible without this driver. 🙁

IoT

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A device that has a temperature sensor in an office might report temperature in degrees Fahrenheit or in degrees Celsius. It is not efficient to configure applications to be able to consume data in all these formats. Instead, the data needs to be collected, transformed, and normalized to create a single logical model so that an application can interact with the different devices in the same way.

The data management component of Platform Service includes a device twin feature and an asset twin feature. The device twin feature lets you take advantage of the collection, transformation, and normalization of different formats of device data into a single logical model. The asset twin feature lets you group different devices together to create a Thing, which is a higher value asset-based data structure. You can even group Things together to create new Things. An application can interact with the logical model, regardless of the data format that is used by the individual devices or Things.

For example, a group of devices that report temperature, humidity, and ambient light can be aggregated into a “Room” Thing to represent the comfort level in a specific office. A number of “Room” Things can be aggregated into a “Floor” Thing to represent all offices on a specific level, and a number of “Floor” Things can be aggregated into a “Building” Thing. By using a Thing abstraction, your application is decoupled from the specifics of how the devices are connected, the format in which the devices publish event data, and how the data is combined.

The explanation above i got from the knowledge center, just to  introduce about a problem i  got last week.

The problem:  When we create device types  we must define a Hardware and a Logical interface. When we create  the interfaces we are modeling the schema of a table were data will be saved. You can define “the fields and his type”. As usual i create my interfaces, devices and put the sensors to send data, but some sensors are not sending one of the variables. For example the data expected was { voltage : value , kwh: value) but the sensor send {voltage: value}.  The data is not saved on the database.

To solve the problem i create a ticket and the answer was to test if a key exists if not save it as a null value.

On the logical interface, for each key i need to put the following (example for kwh) : $exists($event.kwh) ? $event.kwh(null)

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Comunidade

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I setup Node-red to use HTTPS and everything works fine. All HTTPS requests go to default port of Node-red.  Today i need to setup a communication with a client that not support HTTPS, just HTTP.

The solution i found was to setup Nginx as reverse proxy.  Nginx receives the HTTP requests and then forward them to Node-red.

On my Nginx server i just add the following lines

server {
listen 80;
location /reddata {
proxy_pass https://<ipaddress>:port/reddata;
}
}

 

 

IoT Linux

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“ImportError: No module named tensorflow” but you know you installed it? Sometimes you can import packages from the console, but not from the Jupyter notebook? !pip install tensorflow sometimes just does not work?

Googling about similar issues made me realise people are suggesting the thing that won’t work most of the time.

If you are installing packages by running

!conda install tensorflow
# or if you want to use pip
!pip install tensorflow

you are using very fragile commands (if run in notebook) and that’s the reason packages you installed can’t be imported. It is not fine this time

Instead, use these commands:

import sys
!conda install --yes --prefix {sys.prefix} tensorflow
# or if you want to use pip
!{sys.executable} -m pip install tensorflow

and you will not have problems with damn ImportError again.

Found this information on this link https://modelpredict.com/importing-packages-in-jupyter-notebook/

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Sharpening a knife is a skill that everyone who enjoys cooking needs to have. I have several stones for sharpening my knives. In addition to having the correct stones one of the most difficult things is to maintain the angle between the knife and the stone during the sharpening process. There are many videos and even YouTube channels on the subject. A video that caught my attention is below. It shows how to create and use an electronic device to maintain the sharpness angle.

 

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Node-red 1.1 released with several new features

 

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Today i upgrade one server to Domino 11.0.1 from Domino 11.0 on linux.  When the server starts the HTTP  the console show the error bellow:

 

[103028:000002-00007F2CD562E740] 06/18/2020 10:40:45 AM JVM: Java Virtual Machine initialized.
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:45 AM HTTP Server: Java Virtual Machine loaded
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: java.lang.reflect.InvocationTargetException
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: at java.lang.reflect.Method.invoke(Method.java:498)
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: at com.ibm.domino.http.bootstrap.BootstrapOSGIClassLoader.loadClassFromBundle(BootstrapOSGIClassLoader.java:136)
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: at com.ibm.domino.http.bootstrap.BootstrapOSGIClassLoader.launchOSGIFramework(BootstrapOSGIClassLoader.java:88)
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: at com.ibm.domino.http.bootstrap.BootstrapOSGIClassLoader.loadClass(BootstrapOSGIClassLoader.java:63)
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: at java.lang.ClassLoader.loadClass(ClassLoader.java:881)
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: at com.ibm.domino.http.bootstrap.BootstrapClassLoader.findClass(BootstrapClassLoader.java:79)
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: Caused by:
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: java.lang.ClassNotFoundException: No class loader available for the bundle: com.ibm.xsp.domino_11.0.0.20191120-0552 [226]
[103028:000002-00007F2CD562E740] 06/18/2020 10:40:50 AM HTTP JVM: at org.eclipse.osgi.internal.framework.EquinoxBundle.loadClass(EquinoxBundle.java:579)

 

The solution was to delete all content of the folder /opt/lotus/notes/latest/linux/osgi/shared/eclipse/plugins and run the installer again.

Domino Linux

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You need A Fully Qualified Domain Name (FQDN) pointing to a dedicated IP address of the webserver.
This needs to be configured by your DNS administrator or provider.

1 – Install Certbot in Centos 8

sudo curl -O https://dl.eff.org/certbot-auto
chmod 0755 /usr/local/bin/certbot-auto

2 – Configure Nginx server_name on nginx.conf

Edit nginx.conf an change the variable server_name to the same FQDN
of your server for example: server_name www.mysphere.com.br;

3 – Run the certbot command:

Execute sudo /usr/local/bin/certbot-auto –nginx and follow the instructions

Test if your Nginx server using https://<server_name>

IoT Linux web