Reliability of embedded memory is critical for system-on-chips (SoCs). Aging-induced faults manifest in field, and they affect the reliability of embedded memories which occupy the most area of an SoC. By performing a proactive approach that repairs aged memory words in use, the probability of fault occurrence should be minimized. In this paper, we proposed an in-field strategy that proactively repairs aged words as well as correctable words. The reliability is enhanced further by combining an aging test, an in-field repair, and an error correction technique. An adaptive reconfiguration of the memory words, including aged words, correctable words, and uncorrectable words, is implemented with small overhead. A 3-state model that identifies memory cells as healthy, aged, or faulty is newly introduced, and the reliability evaluation using this model demonstrates the effectiveness of the proposed strategy.

In smart cities and urban areas, localized weather monitoring will be a readily available feature. Checking the air quality in small area urban motifs, specifically schools and universities situated near a national primary road and mid to high-rise condominiums with increasing sources of pollutants, e.g. particulate matter (PM), becomes a need for risk assessment. An aerial sensor system, consisting of an unmanned aerial vehicle (UAV) and a sensor payload, is designed and implemented. Measurements for PM concentration are taken at various elevations, and during heavy and light traffic conditions. Results show trends relating PM concentration with elevation and traffic conditions.

Reliability of memory is crucial to overall reliability of SoCs. In our previous work, we enhanced reliability through an adaptive combination of repair and memory word correction, however, it is restricted to the identification of faulty memory words. In this work, we enhance reliability further by considering identification of not only faulty words, but aged words as well. We propose a novel method that adaptively assigns aged and faulty words to functional repair or correction based on their vulnerabilities.

Embedded memory is extensively being used in SoCs, and is rapidly growing in size and density. To keep up with the development pace of nanoscale devices, enhancement methods for yield and reliability must overcome the barriers set forth by advent of new technology. To address the issue of reliability, periodic online field test and repair are implemented by using synergistic approach of employing redundancy and ECC to repair or correct both hard errors and soft errors. In this paper, an online remap strategy for memory repair, which ensures ‘fresh’ memory words are always used until the spare words run out, is proposed. The improvement of reliability for memory architectures and the area overhead introduced by the proposed scheme is evaluated.