With the advent of smart city that embedded with smart technology, namely, smart streetlight, in urban development, the quality of living for citizens has been vastly improved. TALiSMaN is one of the promising smart streetlight schemes to date, however, it possesses certain limitation that led to network congestion and packet dropped during peak road traffic periods. Traffic prediction is vital in network management, especially for real-time decision-making and latency-sensitive application. With that in mind, this paper analyses three real-time short-term traffic prediction models, specifically simple moving average, exponential moving average and weighted moving average to be embedded onto TALiSMaN, that aim to ease network congestion. Additionally, the paper proposes traffic categorisation and packet propagation control mechanism that uses historical road traffic data to manage the network from overload. In this paper, we evaluate the performance of these models with TALiSMaN in simulated environment and compare them with TALiSMaN without traffic prediction model. Overall, weighted moving average showed promising results in reducing the packet dropped while capable of maintaining the usefulness of the streetlight when compared to TALiSMaN scheme, especially during rush hour.

Rural off-grid electrification is always very challenging due to mostly using limited output renewable energy source such as solar power system. Owing to its nature of power generation that depends on weather condition, the reliability in power provision is often affected by uncontrolled overwhelming usage or bad weather condition. Total power system blackout that frequently happens not only disturb the night activity routine but also can be life threatening if the rural community is unable to initiate telephony communication with the outside world during state of emergency due to power outage. In order to reduce the frequency of total system blackout caused by the reasons mentioned, we proposed a priority-based energy distribution scheme to assist the off-grid standalone solar power system to improve the overall operating hours of the critical appliances in rural areas. The scheme takes into consideration of criticality of the home appliances as defined by the rural users, so that the system would distribute power supply based on the current state of the system with an objective to prolong the service availability of the critical appliances that matter the most to the users. The scheme has been evaluated under simulated scenario and has shown a 100% operation availability of the critical appliance is achievable even during bad weather season that has very low solar input.