Social interactions in school and office settings traditionally involve few coordinated physical interactions, and most group engagement centers on sharing electronic screens. Wearable robot companions are a promising new direction for encouraging coordinated physical movement and social interaction in group settings. A UC Santa Cruz researcher has developed a wearable social companion that encourages users to interact via physical movement.

The Internet’s TCP/IP protocol architecture is a layered system design. As such, the functions performed by the TCP/IP protocol suite are implemented at different protocol layers, where each layer provides a specific set of services to the layer above through a well-defined interface. Using this interface, data being received or sent is passed up or down the stack on its way through the network.However, layered design approaches can increase overhead, as each layer incurs additional communication (e.g., additional header field) and processing costs. Furthermore, limiting the flow between layers to data plane information restricts the sharing of control information across layers and may lead to functions being duplicated at different layers. 

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Low noise amplifiers are ubiquitous in wireless data network receivers and radios. Themaximum transmission distance is limited by the receiver noise which is mostly determined by the noise figure of the first amplifier stage, the LNA. Reduction of LNA noise is thus always desirable in that it can increase transmission range or reduce power consumption resulting in higher performance or reduced system cost. This approach lowers the noise of the LNA relative to the other available methods.

The traditional collision avoidance handshake consists of a request-to-send (RTS), clear-to-send (CTS), a data packet, and an acknowledgment (ACK). However, this system can result in multiple access interference on variable-length data packets and acknowledgements. This can even occur in multi-hop wireless networks when hidden terminals, exposed transmitters, or exposed receivers are present. 

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Researchers at the University of California, Davis have developed an approach for integrating quantum computers into the existing internet backbone.

Researchers at the University of California, Davis have developed a phased-locked loop coupled array system capable of generating phase shifts in phased array antenna systems - while minimizing signal losses.

Computer-based, internet-connected, audio/video meeting platforms have become pervasive worldwide, especially since the 2020 emergence of the COVID-19 pandemic lockdown. These meeting platforms include Cisco Webex, Google Meet, GoTo, Microsoft Teams, and Zoom. However, those popular platforms are optimized for meetings in which all the participants are attending the meeting online, individually. Accordingly, those platforms have shortcomings when used for hybrid meetings in which some participants are attending together in-person and others attending online. Also, the existing platforms are problematic for large meetings in big rooms (e.g. classrooms) in which most or all of the participants are in-person. To address those suboptimal meet platform situations, researchers at UC Berkeley conceived systems, methods, algorithms and other software for a meeting platform that's optimized for hybrid meetings and large in-person meetings. The Berkeley meeting platform offers a user experience that's familiar to users of the conventional meeting platforms. Also, the Berkeley platform doesn't require any specialized participant hardware or specialized physical room infrastructure (beyond standard internet connectivity).

The field of autonomous transportation is rapidly evolving to operate in diverse settings and conditions. However, as the number of autonomous vehicles on the road increases the complexity of the computations needed to safely operate all of the autonomous vehicles grows rapidly. across multiple vehicles, this creates a very large volume of computations that must be performed very quickly (e.g., in real or near-real time).   Thus, treating each autonomous vehicle as an independent entity may result in inefficient use of computing resources, as many redundant data collections and computations may be performed (e.g., two vehicles in close proximity may be performing computations related to the same detected object). To address this issue, researches at UC Berkeley proposed algorithms for the management and exchange of shared information across nearby and distant vehicles.According to the proposed arrangement, autonomous vehicles may share data collected by their respective sensor systems with other autonomous vehicles and adjust their operations accordingly in a manner that is more computationally efficient. This can not only increase safety but at the same time reduce computational load required by each individual vehicle.

The field of autonomous transportation is rapidly evolving to operate in diverse settings and conditions.  Critical to the performance of autonomous vehicles is the ability to detect other objects in the autonomous vehicle’s vicinity and adjust accordingly. To do so, many autonomous vehicles utilize a variety of sensors, including sonar. Although these sensor systems have been shown to improve the safety of autonomous vehicles by reducing collisions, the sensor systems tend to be computationally inefficient.  For instance, the sensor systems may generate large volumes of data that must be processed quickly (e.g., in real or near-real time).  The performance of excessive computations may delay the identification and deployment of necessary resources and actions and/or increase the cost of hardware on the vehicle making it less financially appealing to the consumer. Researches at UC Berkeley proposed algorithms for temporally and spectrally adaptive sonar systems for autonomous vehicles. These allow utilization of existing sonar system in an adaptive manner and in interface with existence hardware/software employed on autonomous vehicles. 

Spatial computing experiences are constrained by the real-world surroundings of the user.  In such experiences, augmenting virtual objects to existing scenes require a contextual approach, where geometrical conflicts are avoided, and functional and plausible relationships to other objects are maintained in the target environment.  Yet, due to the complexity and diversity of user environments, automatically calculating ideal positions of virtual content that is adaptive to the context of the scene is considered a challenging task.    UC researchers have developed a framework which augments scenes with virtual objects using an explicit generative model to learn topological relationship from priors extracted from a real-world and/or synthetic 3D datasets.  Primarily designed for spatial computing applications, SceneGen extracts features from rooms into a novel spatial representation which encapsulates positional and orientational relationships of a scene which captures pairwise topology between objects, object groups, and the room.  The AR application iteratively augments objects by sampling positions and orientations across a room to create a probabilistic heat map of where the object can be placed.  By placing objects in poses where the spatial relationships are likely, we are able to augment scenes that are realistic. 

UCLA researchers in the Department of Electrical and Computer Engineering have developed a wirelessly powered frequency-swept spectroscopy sensor.

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Researchers at the University of California, Davis have developed a new class of lasers and amplifiers that uses a CMOS-compatible electronics platform - and can also be applied to nano-amplifiers and nano-lasers applications.

Researchers at the University of California, Davis have developed a multi-wavelength, laser array that generates more precise wavelengths than current technologies. The array also delivers narrow linewidths and can operate athermally.

Researchers at the University of California, Davis have developed a nanophotonic-based platform for signal processing and optical computing in algorithm-based neural networks that is faster and more energy-efficient than current technologies.

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The invention is a technique that provides a novel, reliable and secure cryptography solution for inter-vehicular visible light communication. Through combining unique data as the road roughness and the driving behavior, a symmetric security key is generated for both communicating vehicles. As the data used is unique to the communicating vehicles only, the generated keys are thus unique, securing a reliable communication channel between both vehicles.

With the emergence of the Internet of Things in smart homes and buildings, determining the identity and mobility of people are key to realizing personalized, context-aware and location-based services - such as adjusting lights and temperature as well as setting preferences of electronic devices in the vicinity. Conventional electronic user identification approaches either require proactive cooperation by users or deployment of dedicated infrastructure. Consequently, existing approaches are intrusive, inconvenient, or expensive to ubiquitously implement. For example: biometric identification requires specific hardware and physical interaction; and vision-based (video) approaches need favorable lighting and introduce privacy issues. To address this situation, researchers at UC Berkeley developed an identification system that uses existing, pervasive WiFi infrastructure and users' WiFi-enabled devices. The innovative Berkeley technology cleverly leverages attributes such as the MAC address and RSS of users' WiFi-enabled devices. Furthermore, the Berkeley approach is facilitated by an unsupervised learning scheme that maps each user identification with associated WiFi-enabled devices. This technology could serve as a vital underpinning for practical personalized context-aware and location-based services in the era of the Internet of Things.

Researchers at the University of California, Davis have developed a quarter-rate serial link receiver with low aperture delay samplers for use in high-speed serial link interconnects in network systems. This receiver decreases the parasitic capacitances that result from threshold adjustments and can drastically decrease the amount of power required for high data rate applications.