IoT Data Communication Optimization via Bit Stream Storage
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Solution Overview
Problem
Current IoT devices face challenges in implementing comprehensive standard communication protocols that enhance security and resource utilization while managing secure data communications between IoT devices and servers, particularly in resource-constrained environments, limiting advanced security protocols and efficient firmware updates.
Innovation Solution
The system optimizes data communication by defining data types and compact storage in bit stream concepts using a communication protocol, such as microTLS, to reduce resource requirements and communication overhead, enabling efficient and secure data transmission between IoT devices and servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive standard communication protocols are implemented to enhance security and resource utilization, then security and resource efficiency improve, but device complexity and implementation difficulty increase in resource-constrained environments
Solution Approach 1:
The patent changes the data representation parameters by defining custom data types with specific bit-stream formats (e.g., uint8_t, int16_t, float32_t) and encoding schemes. This allows resource-constrained devices to implement secure communication by transmitting only the necessary number of bits for each data element, reducing overall communication overhead while maintaining security through standardized type definitions and validation rules.
Solution Approach 2:
The patent segments data transmission into structured type definitions and encoded values. Each data element is divided into a type field and a value field, with the type field specifying the data format and the value field containing the actual data in the appropriate encoding. This segmentation allows receiving devices to efficiently parse and validate data without processing unnecessary information, reducing computational complexity while maintaining security.
2Quantity of substance
If data transmission size is reduced to optimize bandwidth usage in low/narrow bandwidth networks, then network efficiency improves, but data representation precision and completeness may deteriorate
Solution Approach 1:
The patent applies parameter changes by selecting appropriate data types and bit depths for each data element based on its precision requirements. For example, it uses uint8_t for integer values requiring 0-255 range, int16_t for values requiring negative numbers or larger ranges, and float32_t for decimal precision. This ensures that each transmitted value uses the minimum necessary bits to maintain its precision requirements while optimizing overall bandwidth utilization.
Solution Approach 2:
The patent applies local quality by assigning different data types and precision levels to different data elements based on their specific requirements. Critical measurements use higher precision types (float32_t, int32_t) while less critical data uses compact types (uint8_t, int16_t). This localized optimization maintains necessary precision for important data while minimizing transmission size for the overall message.
3Use of energy by moving object
If resource-constrained microcontrollers are used in IoT devices, then device cost and power consumption improve, but capability to implement advanced security protocols and firmware updates deteriorates
Solution Approach 1:
The patent extracts and transmits only the essential security-relevant data elements in a standardized format. By defining explicit type definitions for authentication tokens, sensor readings, and control commands, the system enables resource-constrained devices to participate in secure communication protocols without implementing full-featured protocol stacks. The structured data format allows security functions to operate on compact, well-defined data structures rather than complex proprietary formats.
Solution Approach 2:
The patent creates a universal data transmission framework that works across resource-constrained devices with varying capabilities. The type-definition approach provides a common language that simple microcontrollers can use for basic sensor reporting while also supporting more complex data structures for security authentication and firmware update protocols. This multi-functional data format allows the same communication infrastructure to support multiple security and management functions.
Data Source
AI summary
The present subject matter discloses a system and method for optimizing data communication of Internet of Things (IoT) devices. The system comprises a collection of IoT devices, an IoT server, a management console, third party IoT gateways and user devices. The IoT device is connected to a sensor or an actuator. The IoT device identifies attributes of the sensor or the actuator. Further, the IoT device receives raw data generated by the sensor or the actuator. Subsequently, the IoT device defines data types for the raw data based on the attributes and define bit stream storage for the data types. The IoT device may optimize data-transmission size of the data types and bit stream storage using a communication protocol and transmit the raw data to the IoT server. The IoT server may transcode the raw data into a desired format and relay transcoded data to a management console.