QueSSence is comprehensive AI based Intelligent IoT Platform solution that includes a flexible hardware platform, development environment, AI based libraries, cloud software and services framework. The compact QueSSence board includes Redpine’s Wireless Secure MCU (WiSeMCU™) with multi-protocol wireless module providing Wi-Fi, Bluetooth 5.0, and ZigBee connectivity, six-axis inertial sensors, an infrared receiver, a debug port, push-buttons, LEDs, USB ports, and QueSSence QueBlocks expansion connector. The WiSeMCU module runs an embedded TCP/IP networking stack with SSL/TLS/HTTPS security, apart from complete Wi-Fi, BT 5.0, and ZigBee stacks. The expansion headers accommodate a host of other peripheral devices, with a number of peripherals – called ‘QueBlocks’ – already available from Redpine including capacitive touch display, rechargeable battery, and Multi-Sensor(additional sensors). Application development is supported with a choice of development environments and the Redpine hosted cloud framework offers flexible and customizable connectivity, analytics, and user interfaces.
Developers can stack up QueSSence and the QueBlocks to build comprehensive hardware for an exhaustive range of AI based Intelligent IoT applications.
How easy is it for new “QueBlocks” profiles to be added to QueSSence?
QueSSence compatible QueBlocks can be added seamlessly with minimal effort in integrating hardware and software. We are also offering an Arduino compatible shield to facilitate effortless interoperability.
How is QueSSence is different from other AI based Intelligent IoT platforms?
QueSSence is comprehensive AI based Intelligent IoT Platform solution that includes a flexible hardware platform, development environment, AI based libraries, cloud software and services framework. It supports ultra-low power multi-protocol wireless connectivity (Wi-Fi®, BT 5.0, ZigBee) for future proofing of devices. QueSSence includes a highly integrated embedded which connects to popular cloud services platforms without the need for third party proxy services using SSL and OAuth 2. It enables power optimized low power wearable designs. It also includes Physical Unclonable Function (PUF) security and Secure Provisioning allows for enhanced device authentication and hardware software binding.
Using QueSSence, how fast can someone bring a new AI Edge device to market?
Typically, for someone to incorporate wireless capable hardware and integrate the associated software into their system can take anywhere between 2 to 8 months. QueSSence is already equipped with a multi-protocol wireless module, and comes with AI ready to use different AI based Algorithm libraries on the device. The time involved in integrating wireless to a system is thereby reduced considerably. QueSSence also comes with on board sensors like Accerolometer, Gyrometer, which further reduce time and efforts involved in including sensing devices and control abilities into an existing system by mitigating the need to enter into the cycle of procurement, integration and testing altogether.QueSSence is a fully loaded platform using which a product can be taken to market with minimal effort and within a nominal amount of time.
How will QueSSence AI platform change the way Intelligent IoT devices are being developed?
First – fundamental to any Intelligent IoT device is connectivity; and as a first in the market, QueSSence platform natively incorporates all forms of wired and wireless interfaces along with AI capabilities. This saves potentially weeks of effort normally taken in integrating and optimizing a wireless interface into an embedded system.
Second – QueSSence development environment integrates multiple steps in the device design process, and developers will be able to visualize and create the entire product in one flow – including the circuit, hardware, software, and cloud visualization.
Third – for the first time an AI Intelligent IoT development platform does not stop at being that. The core computing and connectivity components of the QueSSence platform are available in a small, highly integrated module from RedpineSignals. Developers will be able to proceed with their form-factor design with assured small size, low price, exact functionality and performance that they have already experienced with QueSSence AI platform.
Is there any licensing needed for QueSSence AI library source code?
The QueSSence code is open. The libraries and projects Redpine provided along with the platform includes all low level parameterization and optimization facilities. In the default architecture, AI Libraries(Basic), the wireless stack and the networking stack resides within the connectivity device in the platform – the RS module. However, other architectures are possible where the networking stack may be the user’s own or a third party’s – running on the MCU within the platform.
For Advanced AI Libraries, User needs to purchase them to download them.
Can third-party developers create and offer QueSSence QueBlocks?
Yes, we are planning to make our QueBlocks requirements public using which the users can create their own QueBlocks. However, these QueBlocks will have to be approved and integrated into the platform by Redpine. Since it is not possible for Redpine to create all possible combination of QueBlocks, this approach will help us in expanding the usage of QueSSence. However, we are also planning to develop a large portfolio of QueBlocks for several AI based Intelligent IoT applications.
What market needs are being addressed with the QueSSence AI platform?
Redpine has been selling its wireless products to IoT customers for several years. Over time, we realized the pain the customers have to go through to integrate hardware and software solutions from different companies. Most of the customers spend majority of their development time in completing the integration of basic components leaving little time for their core application. With QueSSence, we want students/customers to focus on their core strength and leave the rest to QueSSence. This will help them in launching highly differentiated products in a much shorter duration and at a much lower cost.
How does the QueCloud services platform differ from other AI cloud offerings?
Interoperability is one of our key differentiators compared to other cloud services. QueCloud services provide an ecosystem where QueSSence Devices/device manufacturers, application developers, and service providers can discover each other and build sophisticated solutions together without integration pain across vendors or vertical markets.
What communication protocols are supported between devices and QueCloud cloud services?
QueCloud services offer a number of protocols for your devices to communicate: HTTPS over TLS, REST, WebSocket and MQTT,. QueCloud services also support building Cloud Connectors for devices that use their own third-party cloud.