In our rapidly evolving digital age, traditional concepts such as copyright are being rigorously tested. The advent of Artificial Intelligence (AI), in particular, has initiated a crucial debate on the validity and efficacy of existing copyright laws. This debate becomes particularly intense when we consider the striking difference in the treatment of photographs and AI-generated art under current copyright laws. This discrepancy calls into question our collective understanding of creativity, ownership, and the essence of copyright itself. Is it time for us to reevaluate the concept of copyright in the digital era?
The rise of AI and automation is disrupting industries and transforming the way we work. But instead of mourning the loss of jobs, we should embrace the opportunity to reshape our lives and focus on what we genuinely value.
Security is an important topic for the Internet of Things, and there are several considerations to secure device identity. A good practice is to use secure protocols (such as TLS or DTLS) for transmitting any sensitive information over the network and to ensure that passwords and other sensitive information are securely stored.
This article will provide an example of using X.509 client certificates for connecting to Azure IoT, using the Nordic Thingy:91 platform. The certificates are securely loaded directly to the device, so they are not exposed in the device firmware.
Using certificates allows a hierarchy of trust to be established, allowing system owners to delegate certificate management to third parties while retaining control of the root trust.
Network address translation 6-to-4 (NAT64, RFC 6146) is a transition technology that can be used, in conjunction with DNS64 (domain name system 6-to-4, RFC 6147), to replace NAT44 in dual-stack networks, and allowing support of IPv6 only devices.
Dual stack is a common deployment solution for adding IPv6 for both consumer and corporate networks, although IPv6-only is becoming more common, with the typical guidance being "IPv6-Only Where You Can, Dual-Stack Where You Must"
Even if you are still stuck in dual stack, it still makes sense to use some of the IPv4 as a Service technologies, such as NAT64 and DNS64, which have the upside of allowing you to support IPv6 only devices, and no downside. As an additional benefit, you also get valuable experience in IPv6 systems.
The cost is that you need to have infrastructure that supports NAT64, either provided by your ISP, or from your own networking equipment/router. This is not as much an issue for DNS64, as public DNS64 is available, e.g. Google.
If your network supports it, look at implementing NAT64 + DNS64 today; if it does not, contact your equipment provider to find out when they will support this important technology for IPv6.
Thread is a mesh networking stack running on 6LoWPAN (IPv6 over Low-Power Wireless Personal Area Networks) over IEEE 802.15.4 radios. To connect to the broader network, a Thread Border Router is required, which acts as a gateway between the Thread mesh radio network and upstream networks.
Thread, especially when used with Matter, is an important development for home automation, however the technologies also have commercial applications. The initial commercial focus of Thread is for smart buildings.
The networking layer sits between the underlying physical network, and the application layers on top.
Matter is an application protocol for device automation that runs on top of Thread (and also WiFi), with Bluetooth used for device commissioning. Matter 1.0 was also released in October 2022 and is supported by major home automation vendors (Google, Amazon, Apple, and Samsung), but can also be used in commerical deployments.
When provisioning a Matter device to a Thread mesh, Bluetooth is used for the initial provisioning and sets up both the connection the the Thread mesh and registration in the Matter Hub. One important aspect of Matter is multi-admin, allowing one device to be controlled by multiple hubs.
The layered approach means Thread can be used by itself, providing mesh networking for smart buildings using other protocols, or in conjunction with Matter.
The article also looks at setting up a OpenThread Border Router for testing, and shows provisions a Matter test device to the Thread mesh.
M5Stack produce a suite of pilot-suitable modular IoT devices, including the Atom DTU NB-IoT. The NB-IoT DTU (Narrow Band Internet of Things - data transmission unit) comes in a small 64 24 29mm case with a DIN rail clip on mounting and support for RS-485 including 9-24V power (or USB-C power).
The kit base has a SIM7020G modem and the ESP32-based Atom Lite (which also supports WiFi) is included with a very resonable price. The device has built in MQTT, supports secure public certificate TLS connections, and supports IPv6.
While the physical unit is ready for pilot deployment (and the M5Stack website has several commerical deployment case studies), there is no pre-written firmware for the device, so some up front development is needed.
As well as reviewing the strengths and weaknesses of the device, I will also provide some sample code for a proof-of-concept using an Env III environment sensor to transmit temperature, humidity, and air pressure to an MQTT test server using MQTTS (with server certificates), over IPv6, over NB-IoT.
The Dragino NBSN95/NBSN95A family is a deployment-ready range of water resistant NB-IoT (Narrow Band Internet of Things) devices that are available pre-packaged with various sensors such as soil moisture, distance detection, liquid level, and temperature/humidity sensors.
NB-IoT is a Low-Power Wide-Area Network (LPWAN) technology that allows devices to be accessed in remote locations and operate on battery for long periods of time, up to many years.
In this article we will look a the N95S31B, the model with the pre-packaged temperature/humidity sensors, the strengths and weaknesses of the device, and then walk through configuing the device and see it connect to an MQTT test server. Our previous article showed you how to set up an MQTT test server on Azure if needed.
The NBSN95 is an open source project, with both the software and hardware specifications available, if you need to customise the application. We have also previously reviewed the Dragion LDDS75 LoRaWAN device.
MQTT (originally Message Queuing Telemetry Transport) is an important protocol for IoT that has been widely adopted. Devices deployed to the field may be connecting to existing MQTT endpoints, however you may also want to deploy your own MQTT server for testing purposes.
This article shows you how to deploy an Eclipse Mosquitto MQTT server onto Azure, configured for secure connections (MQTTS, which is MQTT over TLS), accessible over the internet, and including support for both IPv6 and legacy IPv4.
First we will configure a network in Azure, then deploy the server, and then test the deployment.
The instructions below show the individual commands, but if you want a quick start then full scripts, with automatic parameters, are available on Github https://github.com/sgryphon/iot-demo-build/blob/main/azure-mosquitto/README-mosquitto.md
To deploy the network and then server components via the scripts:
az login az account set --subscription <subscription id> $VerbosePreference = 'Continue' ./azure-landing/infrastructure/deploy-network.ps1 ./azure-mosquitto/infrastructure/deploy-mosquitto.ps1 YourSecretPassword
Read on for the full details.
In this post we will cover how to the the built in support for OpenTelemetry in modern .NET to instrument your distributed application for tracing and logging, how the OpenTelemetry Collector can be used to simplify instrumention, and how the OpenTelemetry Protocol is building a (brilliant) connected future.
We will now go further than logging and look at tracing. Tracing looks at the different units of work (spans) done during an operation (trace), how they are connected, and the timings of the different components. This is an important tool for investigating performance issues in distributed systems.
An example distributed trace timeline, across multiple components, viewed in Jaeger, one of many supported tools:
As well as looking at individual traces timings can be aggregated across the system to find the slowest areas, and identify anomalies.
LoRaWAN devices are a popular solution for IoT, with many benefits, but they cannot connect directly to Azure IoT.
LoRaWAN devices communicate using LoRa to a local LoRaWAN gateway, which then communicates using standard protocols to a LoRaWAN network server. Only then can it be converted to a suitable IP-based protocol to connect to Azure IoT.
Even if they did share a common network, LoRaWAN IoT devices are often small, low-power, battery operated devices that operate in short bursts of minimal communication, and not the verbose communication expected by Azure IoT, so you would want to use a gateway anyway.
To test out connecting field-ready LoRaWAN devices to Azure IoT, I ordered a Dragino LDDS75 LoRaWAN Distance Detection Sensor, used to measure the distance between the sensor and a flat object. It can be used for both horizontal and vertical distance measuring, such as liquid level measurement or object detection (e.g. parking space).
The Dragino platform uses open source hardware, with Dragino schematics and details fully available on github, although you are probably better off purchasing one than trying to build it yourself.
I set up the device up using The Things Network, a community network suitable for small scale testing, connected to Azure IoT.