This research work proposes a method for the securing and monitoring of petroleum product distribution records in a decentralized ledger database using blockchain technology. The aim of using this technique is to secure the transaction of distributed ledgers in a database and to protect records from tampering, fraudulent activity, and corruption by the chain participants. The blockchain technology approach offers an efficient security measure and novel advantages, such as in the transaction existence and distribution ledger management between the depot, transporter, and retailing filling station. Others advantages are transparency, immunity to fraud, insusceptibility to tampering, and maintaining record order. The technique adopted for this secure distributed ledger database is crypto hash algorithm-1 (SHA-1)-based public permissioned blockchain and telematics, while this telematics approach is an embedded system integrated into an in-vehicle model for remote tracking of geolocation (using Global Positioning System (GPS)), monitoring, and far-off data acquisition in a real-time. The scope of the data in the secure distributed ledger database (using blockchain) developed are identification (ID) of the tanker operator, Depot name, Source station ID, Destination station ID, Petroleum product volume, Transporter ID, and Geographic automobiles location. This system proved to be efficient, secure, and easy to maintain as it does not permit any individual for records tampering, but supports agreement of ~75% of participants in the chain to make changes.

-Human vital physiological parameters (HVPP) monitoring with embedded sensors integration has improved the smart system technology in this era of a ubiquitous platform. Several IoT-based healthcare applications have been proposed for remote health monitoring. Most of the devices developed require one on one contact with doctors before any medical diagnosis is undertaken which make it difficult for frequent visitation to the health center. In this paper, embedded heartbeat and temperature sensors for remote monitoring have been developed using Arduino lily as the system controller and processing unit. The Bluetooth low power enables with Android mobile apps is used for remote monitoring and communication of HVPP in a real time. This gives medical personnel and individual customers opportunity of monitoring their vital physiological parameters such as heartbeat rate and body temperature. However, it moderates sudden attack of chronic ailment like hypertension and reduces congestion of patient in the hospitals.

Nowadays, demand for low power, small, mobile and flexible computing machines that interconnects are growing rapidly. This study highlights internet of things (IoT) model regarding sensor node discovery and IPV6 framework using 6LoWPAN. Contiki network simulator (cooja) was used to examine the performance of the proposed network. The simulator was chosen because it provides good graphical user interface environment and allow rapid simulation setup found to be best in simulating network involving 6LoWPAN. Three experiments were carry out with the network topology designed to have 3, 7 and 5 motes respectively. The parameters considered in the simulation were throughput and packet loss which were examined using packet generation rate of 1 to 50 packet/sec with a constant delay. GET requests was sent to the humidity and temperature sensor motes running CoAP servers, and the corresponding throughput were observed in each case per experiment, it was observed that there was a 10 packet per second increase before it finally dropped This was because of the packet loss due to the increase in traffic. GET request was sent to motes to obtain the packet loss and the packet that were not acknowledged determined the packet loss. In this study, the performance of the proposed model in terms of throughput and packet loss was studied and the expected results will aid in planning 6LoWPAN network, A transition flow diagram was evolved for this work to represent packet routing process.

This paper tends to address the problem of having to track devices within an indoor location, Spatial analysis of signal with respect to particular location was carried out, it deploys the use of IEEE 802.11b WLAN Protocol. CDMA is adopted as its multiple access technique , a commonly used term FINGERPRINT used in indoor geolocation system technique seek to exploit the relationship between measurable physical stimulus and a specific location. Comparison between simulation result and mathematical model was carried out.

Abstract-In the mobile radio environment, signals are usually impaired by fading and multipath delay phenomenon. This work modeled and simulates OFDM in a wireless environment, it also illustrates adaptive modulation and coding over a dispersive multipath fading channel whereby simulation varies the result dynamically. Dynamic approach entails adopting probabilistic approach to determining channel allocation; First an OFDM network environment is modeled to get a clear picture of the OFDM concept. Next disturbances such as noise are deliberately introduced into systems that are both OFDM modulated and non-OFDM modulated to see how the system reacts. This enables comparison of the effect of noise on OFDM signals and non-OFDM modulated signals. Finally efforts are made using digital encoding schemes such as QAM and DPSK to reduce the effects of such disturbances on the transmitted signals. In the mobile radio environment, signals are usually impaired by fading and multipath delay phenomenon. In such channels, severe fading of the signal amplitude and inter-symbol-interference (ISI) due to the frequency electivity of the channel cause an unacceptable degradation of error performance. Orthogonal frequency division multiplexing (OFDM) is an efficient scheme to mitigate the effect of multipath channel.

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Over the last three decades, the global population of human beings has increased at an exponential rate, resulting in an equal rise in the number of vehicles owned and used globally. Vehicle traffic is a major economic component in both urban and rural areas, and it requires proper management and monitoring to ensure that this mass of vehicles coexists as smoothly as possible. The amount of vehicular traffic on roads around the world, with Nigeria as a case study, results in varying degrees of traffic rule violations, especially red light jumping.  To arrest offenders and resolve the weaknesses and failures of human traffic operators who cannot be everywhere at once, efficient traffic violation and number plate recognition systems are needed. There are several methods for reading characters, which can be alphabets, numbers, or alphanumeric. To minimize processing time and computational load on the machine, this research proposed k-Nearest Neighbour for plate number character recognition. The system was developed and evaluated. From the result, the localization of license plate regions within an image was 92 percent accurate, and character recognition was 73 percent accurate.