Different people have different visions for the Internet of Things, but it essentially boils down to the networking of embedded devices in everyday appliances, as well as new devices which can provide additional benefits or services:
The Internet of Things (IoT) is the interconnection of uniquely identifiable embedded computing devices within the existing Internet infrastructure.
At Emdalo Technologies, we have embraced this trend and our recent projects have have focused on delivery of minimal wireless network stacks for extended operation in low-power and resource-constrained environments. Without compromising on data security.
Having a team which has extensive experience in all of the technology/product sectors required to deliver an efficient and secure IoT offering is a distinct advantage. From driver development for new or existing sensor/control technology to providing the communications infrastructure required for the use of those sensors/controllers, Emdalo has the experience to deliver or consult on a full end to end system development process to suit your needs.
We are working with leading silicon providers, social media, and specialist IoT cloud providers to deliver solutions for our customers. For further details, please contact us to discuss how to utilize Emdalo's expertise to solve your particular issues.
At Emdalo, we consider information security a cornerstone of the IoT experience. If you don't know where to start with securing your network communications, we can advise on the many options and ease-of-use/security tradeoffs. For more informed customers, we can offer advice to account for recent advances, as different algorithms or designs are compromised.
We have expereience in analyzing different threat scenarios and securing those use cases. We have worked with various technologies, such as:
The proliferation of [intelligent] embedded devices has led to a surge in computational requirements for an increasingly greater number of applications. Natural language processing, facial recognition, computer vision and automatically learning systems of networked devices are just some of features being packed into devices with limited resources and power usage.
Machine Learning (ML) refers to a number of algorithmic approaches that can be employed to allow a program to be trained or to learn independently in order to provide useful predictions about the associated data. We have experience with Facial Recognition, Structure from Motion, Human-Computer Interaction, and Computer Vision.